srujan00123
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End of training
Browse files- README.md +67 -0
- config.json +110 -0
- preprocessor_config.json +9 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-medical-speed
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-large-medical-speed
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This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4703
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- Wer: 0.1992
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 30
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 3.9919 | 3.97 | 500 | 3.0791 | 0.9895 |
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| 1.6651 | 7.94 | 1000 | 0.5613 | 0.4259 |
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| 0.4694 | 11.9 | 1500 | 0.4658 | 0.2835 |
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| 0.2812 | 15.87 | 2000 | 0.5245 | 0.2460 |
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| 0.1923 | 19.84 | 2500 | 0.4438 | 0.2300 |
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| 0.1406 | 23.81 | 3000 | 0.5112 | 0.2121 |
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| 0.1082 | 27.78 | 3500 | 0.4703 | 0.1992 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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config.json
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{
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"_name_or_path": "facebook/wav2vec2-large",
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"activation_dropout": 0.1,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"add_adapter": false,
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"apply_spec_augment": true,
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"architectures": [
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"Wav2Vec2ForCTC"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"classifier_proj_size": 256,
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"codevector_dim": 768,
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"contrastive_logits_temperature": 0.1,
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"conv_bias": false,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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],
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"conv_stride": [
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5,
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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"do_stable_layer_norm": false,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_dropout": 0.0,
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"feat_extract_norm": "group",
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"feat_proj_dropout": 0.1,
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"feat_quantizer_dropout": 0.0,
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"final_dropout": 0.1,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"model_type": "wav2vec2",
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"num_adapter_layers": 3,
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"num_attention_heads": 16,
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"num_codevector_groups": 2,
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"num_codevectors_per_group": 320,
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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"num_hidden_layers": 24,
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id": 31,
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"proj_codevector_dim": 768,
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"tdnn_dilation": [
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],
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"tdnn_dim": [
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512,
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512,
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512,
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512,
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],
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"tdnn_kernel": [
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],
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"torch_dtype": "float32",
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"transformers_version": "4.34.1",
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"use_weighted_layer_sum": false,
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"vocab_size": 32,
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"xvector_output_dim": 512
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": false,
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"sampling_rate": 16000
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b6fd69d7d2102cea6a12d4501849b1d7d0c232db8cd4e4b02df295a36ea52e37
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size 1261988062
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:788a6b106d14f2ef205b74512bec691d27ee78066cdf45673e63bbd0f7499873
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size 4472
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