---
license: apache-2.0
base_model: vitouphy/wav2vec2-xls-r-300m-english
tags:
- generated_from_trainer
model-index:
- name: wav2vec
  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. -->

# wav2vec

This model is a fine-tuned version of [vitouphy/wav2vec2-xls-r-300m-english](https://huggingface.co/vitouphy/wav2vec2-xls-r-300m-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 417.9874
- Pcc Accuracy: 0.2482
- Pcc Fluency: 0.2791
- Pcc Total Score: 0.3110
- Pcc Content: 0.3780

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.4
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 3176.8777     | 1.01  | 100  | 2967.8770       | 0.2384       | 0.1513      | -0.2037         | -0.0386     |
| 3000.9279     | 2.02  | 200  | 2907.2825       | 0.2949       | 0.1813      | -0.1250         | 0.0827      |
| 2716.2498     | 3.03  | 300  | 2805.8979       | 0.3034       | 0.2123      | 0.0290          | 0.2344      |
| 2600.8768     | 4.04  | 400  | 2666.0171       | 0.2859       | 0.2345      | 0.1642          | 0.3183      |
| 2222.3631     | 5.05  | 500  | 2490.9263       | 0.2698       | 0.2475      | 0.2305          | 0.3488      |
| 1940.7414     | 6.06  | 600  | 2284.4573       | 0.2573       | 0.2552      | 0.2588          | 0.3591      |
| 1962.4018     | 7.07  | 700  | 2051.6846       | 0.2504       | 0.2603      | 0.2738          | 0.3635      |
| 1506.0297     | 8.08  | 800  | 1798.2383       | 0.2444       | 0.2633      | 0.2813          | 0.3653      |
| 1448.3059     | 9.09  | 900  | 1534.5461       | 0.2396       | 0.2662      | 0.2845          | 0.3650      |
| 1202.578      | 10.1  | 1000 | 1265.2390       | 0.2376       | 0.2678      | 0.2873          | 0.3647      |
| 917.5093      | 11.11 | 1100 | 1021.2091       | 0.2356       | 0.2697      | 0.2896          | 0.3651      |
| 781.4407      | 12.12 | 1200 | 825.2852        | 0.2340       | 0.2710      | 0.2901          | 0.3647      |
| 633.8744      | 13.13 | 1300 | 674.1681        | 0.2337       | 0.2724      | 0.2918          | 0.3652      |
| 554.5075      | 14.14 | 1400 | 573.6318        | 0.2354       | 0.2737      | 0.2954          | 0.3677      |
| 500.6607      | 15.15 | 1500 | 510.6489        | 0.2378       | 0.2740      | 0.2978          | 0.3700      |
| 472.1874      | 16.16 | 1600 | 468.3256        | 0.2394       | 0.2751      | 0.3012          | 0.3720      |
| 406.9743      | 17.17 | 1700 | 444.8770        | 0.2421       | 0.2763      | 0.3041          | 0.3739      |
| 373.2401      | 18.18 | 1800 | 432.6308        | 0.2438       | 0.2771      | 0.3068          | 0.3751      |
| 447.599       | 19.19 | 1900 | 425.9487        | 0.2457       | 0.2778      | 0.3081          | 0.3762      |
| 360.8572      | 20.2  | 2000 | 421.8146        | 0.2466       | 0.2786      | 0.3093          | 0.3772      |
| 409.8801      | 21.21 | 2100 | 420.0713        | 0.2473       | 0.2786      | 0.3100          | 0.3777      |
| 419.8665      | 22.22 | 2200 | 418.7286        | 0.2478       | 0.2791      | 0.3107          | 0.3778      |
| 369.3772      | 23.23 | 2300 | 418.1939        | 0.2477       | 0.2791      | 0.3105          | 0.3776      |
| 449.1843      | 24.24 | 2400 | 417.9874        | 0.2482       | 0.2791      | 0.3110          | 0.3780      |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1