---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0216
- Wer: 1.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---:|
| 6.0993        | 0.5714  | 100  | 3.1919          | 1.0 |
| 2.9332        | 1.1429  | 200  | 3.0675          | 1.0 |
| 2.878         | 1.7143  | 300  | 3.1538          | 1.0 |
| 2.873         | 2.2857  | 400  | 2.9688          | 1.0 |
| 2.8574        | 2.8571  | 500  | 3.0386          | 1.0 |
| 2.859         | 3.4286  | 600  | 3.0947          | 1.0 |
| 2.8631        | 4.0     | 700  | 3.2471          | 1.0 |
| 2.8612        | 4.5714  | 800  | 2.9827          | 1.0 |
| 2.8592        | 5.1429  | 900  | 3.0277          | 1.0 |
| 2.8617        | 5.7143  | 1000 | 3.1227          | 1.0 |
| 2.8644        | 6.2857  | 1100 | 3.0502          | 1.0 |
| 2.8618        | 6.8571  | 1200 | 3.0055          | 1.0 |
| 2.8638        | 7.4286  | 1300 | 3.0646          | 1.0 |
| 2.8608        | 8.0     | 1400 | 3.1780          | 1.0 |
| 2.8585        | 8.5714  | 1500 | 2.9719          | 1.0 |
| 2.8624        | 9.1429  | 1600 | 3.0521          | 1.0 |
| 2.8588        | 9.7143  | 1700 | 3.0839          | 1.0 |
| 2.8594        | 10.2857 | 1800 | 3.1120          | 1.0 |
| 2.8566        | 10.8571 | 1900 | 2.9648          | 1.0 |
| 2.8587        | 11.4286 | 2000 | 3.0812          | 1.0 |
| 2.8588        | 12.0    | 2100 | 3.1690          | 1.0 |
| 2.8607        | 12.5714 | 2200 | 2.9951          | 1.0 |
| 2.8561        | 13.1429 | 2300 | 3.0317          | 1.0 |
| 2.8565        | 13.7143 | 2400 | 3.0880          | 1.0 |
| 2.8638        | 14.2857 | 2500 | 3.0978          | 1.0 |
| 2.8563        | 14.8571 | 2600 | 2.9716          | 1.0 |
| 2.8592        | 15.4286 | 2700 | 3.0461          | 1.0 |
| 2.859         | 16.0    | 2800 | 3.1339          | 1.0 |
| 2.8584        | 16.5714 | 2900 | 3.0304          | 1.0 |
| 2.8562        | 17.1429 | 3000 | 2.9964          | 1.0 |
| 2.8574        | 17.7143 | 3100 | 3.0665          | 1.0 |
| 2.8609        | 18.2857 | 3200 | 3.1042          | 1.0 |
| 2.8564        | 18.8571 | 3300 | 2.9905          | 1.0 |
| 2.8601        | 19.4286 | 3400 | 3.0030          | 1.0 |
| 2.8562        | 20.0    | 3500 | 3.1000          | 1.0 |
| 2.8565        | 20.5714 | 3600 | 3.0409          | 1.0 |
| 2.8566        | 21.1429 | 3700 | 2.9837          | 1.0 |
| 2.8577        | 21.7143 | 3800 | 3.0294          | 1.0 |
| 2.8554        | 22.2857 | 3900 | 3.0737          | 1.0 |
| 2.854         | 22.8571 | 4000 | 3.0101          | 1.0 |
| 2.8556        | 23.4286 | 4100 | 3.0014          | 1.0 |
| 2.8557        | 24.0    | 4200 | 3.0693          | 1.0 |
| 2.8531        | 24.5714 | 4300 | 3.0308          | 1.0 |
| 2.8552        | 25.1429 | 4400 | 3.0050          | 1.0 |
| 2.8536        | 25.7143 | 4500 | 3.0215          | 1.0 |
| 2.855         | 26.2857 | 4600 | 3.0509          | 1.0 |
| 2.8513        | 26.8571 | 4700 | 3.0163          | 1.0 |
| 2.8533        | 27.4286 | 4800 | 3.0170          | 1.0 |
| 2.8552        | 28.0    | 4900 | 3.0345          | 1.0 |
| 2.8521        | 28.5714 | 5000 | 3.0259          | 1.0 |
| 2.8522        | 29.1429 | 5100 | 3.0219          | 1.0 |
| 2.8543        | 29.7143 | 5200 | 3.0216          | 1.0 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1