---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-medical-speed
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-medical-speed

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4703
- Wer: 0.1992

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.9919        | 3.97  | 500  | 3.0791          | 0.9895 |
| 1.6651        | 7.94  | 1000 | 0.5613          | 0.4259 |
| 0.4694        | 11.9  | 1500 | 0.4658          | 0.2835 |
| 0.2812        | 15.87 | 2000 | 0.5245          | 0.2460 |
| 0.1923        | 19.84 | 2500 | 0.4438          | 0.2300 |
| 0.1406        | 23.81 | 3000 | 0.5112          | 0.2121 |
| 0.1082        | 27.78 | 3500 | 0.4703          | 0.1992 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1