End of training
Browse files- README.md +68 -0
- config.json +43 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +13 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-multilingual-cased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: punjabi-distilbert-ner
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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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# punjabi-distilbert-ner
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0787
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- Precision: 0.7618
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- Recall: 0.7452
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- F1: 0.7534
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- Accuracy: 0.9777
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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: 2e-05
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- train_batch_size: 16
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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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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0743 | 1.0 | 807 | 0.0794 | 0.6756 | 0.7653 | 0.7176 | 0.9731 |
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| 0.0463 | 2.0 | 1614 | 0.0752 | 0.7545 | 0.7437 | 0.7491 | 0.9772 |
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| 0.0371 | 3.0 | 2421 | 0.0787 | 0.7618 | 0.7452 | 0.7534 | 0.9777 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "distilbert-base-multilingual-cased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "O",
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"1": "I-PER",
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"2": "I-ORG",
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"3": "I-LOC",
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"4": "B-PER",
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"5": "B-ORG",
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"6": "B-LOC"
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},
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"initializer_range": 0.02,
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"label2id": {
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"B-LOC": 6,
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"B-ORG": 5,
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"B-PER": 4,
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"I-LOC": 3,
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"I-ORG": 2,
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"I-PER": 1,
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"O": 0
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"output_past": true,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.33.1",
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"vocab_size": 119547
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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 sha256:9b7cb532239d69e580cac124d03b7555966790cdddb12ed2e5d2ace26124607a
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size 538992677
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:4c53ed7b3350f472e9c9f7b57f8054701bdb2747aa18cffead0c22b1fc345cbd
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size 4027
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vocab.txt
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