---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vecvanilla_ctc_zero_infinity
  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. -->

# wav2vecvanilla_ctc_zero_infinity

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8214
- Wer: 0.3168

## 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: 4
- 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: 500
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4684        | 0.43  | 100  | 1.0567          | 0.4018 |
| 1.2572        | 0.85  | 200  | 0.9726          | 0.3706 |
| 1.139         | 1.28  | 300  | 0.9748          | 0.3602 |
| 1.0956        | 1.71  | 400  | 0.9989          | 0.3619 |
| 1.0891        | 2.14  | 500  | 0.9133          | 0.3606 |
| 1.063         | 2.56  | 600  | 0.9272          | 0.3548 |
| 1.0339        | 2.99  | 700  | 1.0183          | 0.3444 |
| 0.9709        | 3.42  | 800  | 0.8244          | 0.3488 |
| 0.958         | 3.85  | 900  | 0.8335          | 0.3410 |
| 0.8954        | 4.27  | 1000 | 0.8641          | 0.3336 |
| 0.8735        | 4.7   | 1100 | 0.8671          | 0.3306 |
| 0.8411        | 5.13  | 1200 | 0.8373          | 0.3281 |
| 0.805         | 5.56  | 1300 | 0.8197          | 0.3198 |
| 0.8452        | 5.98  | 1400 | 0.8343          | 0.3158 |
| 0.8078        | 6.41  | 1500 | 0.8392          | 0.3165 |
| 0.7946        | 6.84  | 1600 | 0.8214          | 0.3168 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2