---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vecvanilla_ctc_zero_infinity_longertrain
  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_longertrain

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: 1.1396
- Wer: 0.2973

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4721        | 0.43  | 100  | 1.0565          | 0.4014 |
| 1.2574        | 0.85  | 200  | 0.9707          | 0.3704 |
| 1.1397        | 1.28  | 300  | 0.9644          | 0.3609 |
| 1.0939        | 1.71  | 400  | 0.9610          | 0.3637 |
| 1.0874        | 2.14  | 500  | 0.9508          | 0.3581 |
| 1.0573        | 2.56  | 600  | 0.8865          | 0.3518 |
| 1.0386        | 2.99  | 700  | 1.0304          | 0.3493 |
| 0.9792        | 3.42  | 800  | 0.8235          | 0.3523 |
| 0.9789        | 3.85  | 900  | 0.8404          | 0.3388 |
| 0.9095        | 4.27  | 1000 | 1.0925          | 0.3588 |
| 0.8947        | 4.7   | 1100 | 1.0126          | 0.3357 |
| 0.8571        | 5.13  | 1200 | 1.1404          | 0.3550 |
| 0.8276        | 5.56  | 1300 | 0.8135          | 0.3294 |
| 0.8631        | 5.98  | 1400 | 0.8342          | 0.3279 |
| 0.8134        | 6.41  | 1500 | 0.8524          | 0.3177 |
| 0.8027        | 6.84  | 1600 | 0.8182          | 0.3207 |
| 0.7556        | 7.26  | 1700 | 0.8445          | 0.3185 |
| 0.737         | 7.69  | 1800 | 0.8919          | 0.3197 |
| 0.7398        | 8.12  | 1900 | 0.8115          | 0.3167 |
| 0.7069        | 8.55  | 2000 | 0.8346          | 0.3174 |
| 0.7206        | 8.97  | 2100 | 0.9714          | 0.3147 |
| 0.6946        | 9.4   | 2200 | 0.8138          | 0.3124 |
| 0.6752        | 9.83  | 2300 | 0.8366          | 0.3086 |
| 0.7256        | 10.26 | 2400 | 0.8482          | 0.3044 |
| 0.7063        | 10.68 | 2500 | 0.8997          | 0.3041 |
| 0.6399        | 11.11 | 2600 | 0.8614          | 0.3045 |
| 0.6268        | 11.54 | 2700 | 0.8564          | 0.3018 |
| 0.6665        | 11.97 | 2800 | 0.8531          | 0.3006 |
| 0.622         | 12.39 | 2900 | 0.8759          | 0.3007 |
| 0.6568        | 12.82 | 3000 | 1.3093          | 0.3023 |
| 0.6296        | 13.25 | 3100 | 1.1312          | 0.3002 |
| 0.6448        | 13.68 | 3200 | 1.1779          | 0.2994 |
| 0.6188        | 14.1  | 3300 | 1.1203          | 0.2989 |
| 0.6216        | 14.53 | 3400 | 1.1421          | 0.2978 |
| 0.6238        | 14.96 | 3500 | 1.1396          | 0.2973 |


### Framework versions

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