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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec-large-en
  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-large-en

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.2821
- 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---:|
| 6.0558        | 0.7042  | 100  | 7.1035          | 1.0 |
| 5.3678        | 1.4085  | 200  | 7.4719          | 1.0 |
| 5.2548        | 2.1127  | 300  | 7.3891          | 1.0 |
| 5.1982        | 2.8169  | 400  | 7.2118          | 1.0 |
| 5.1951        | 3.5211  | 500  | 7.0877          | 1.0 |
| 5.1829        | 4.2254  | 600  | 7.2987          | 1.0 |
| 5.1937        | 4.9296  | 700  | 7.3988          | 1.0 |
| 5.1905        | 5.6338  | 800  | 7.3964          | 1.0 |
| 5.2445        | 6.3380  | 900  | 7.2698          | 1.0 |
| 5.139         | 7.0423  | 1000 | 7.1558          | 1.0 |
| 5.1925        | 7.7465  | 1100 | 7.2421          | 1.0 |
| 5.2231        | 8.4507  | 1200 | 7.2611          | 1.0 |
| 5.2901        | 9.1549  | 1300 | 7.3504          | 1.0 |
| 5.0849        | 9.8592  | 1400 | 7.3211          | 1.0 |
| 5.3853        | 10.5634 | 1500 | 7.1273          | 1.0 |
| 5.2707        | 11.2676 | 1600 | 7.2369          | 1.0 |
| 5.1156        | 11.9718 | 1700 | 7.3677          | 1.0 |
| 5.1589        | 12.6761 | 1800 | 7.3260          | 1.0 |
| 5.1839        | 13.3803 | 1900 | 7.2956          | 1.0 |
| 5.3138        | 14.0845 | 2000 | 7.1808          | 1.0 |
| 5.2344        | 14.7887 | 2100 | 7.2265          | 1.0 |
| 5.1787        | 15.4930 | 2200 | 7.3030          | 1.0 |
| 5.1879        | 16.1972 | 2300 | 7.2975          | 1.0 |
| 5.106         | 16.9014 | 2400 | 7.2839          | 1.0 |
| 5.3462        | 17.6056 | 2500 | 7.2212          | 1.0 |
| 5.0687        | 18.3099 | 2600 | 7.2478          | 1.0 |
| 5.1134        | 19.0141 | 2700 | 7.2222          | 1.0 |
| 5.1133        | 19.7183 | 2800 | 7.3043          | 1.0 |
| 5.2053        | 20.4225 | 2900 | 7.3150          | 1.0 |
| 5.205         | 21.1268 | 3000 | 7.2460          | 1.0 |
| 5.2558        | 21.8310 | 3100 | 7.2312          | 1.0 |
| 5.215         | 22.5352 | 3200 | 7.2725          | 1.0 |
| 5.1499        | 23.2394 | 3300 | 7.2609          | 1.0 |
| 5.152         | 23.9437 | 3400 | 7.3052          | 1.0 |
| 5.2532        | 24.6479 | 3500 | 7.2958          | 1.0 |
| 5.3097        | 25.3521 | 3600 | 7.2818          | 1.0 |
| 5.1221        | 26.0563 | 3700 | 7.2260          | 1.0 |
| 5.2023        | 26.7606 | 3800 | 7.2648          | 1.0 |
| 5.1029        | 27.4648 | 3900 | 7.2708          | 1.0 |
| 5.085         | 28.1690 | 4000 | 7.2965          | 1.0 |
| 5.2273        | 28.8732 | 4100 | 7.2845          | 1.0 |
| 5.2394        | 29.5775 | 4200 | 7.2821          | 1.0 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1