---
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8842
- 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---:|
| No log        | 0.3521  | 50   | 6.2209          | 1.0 |
| 7.7114        | 0.7042  | 100  | 5.8125          | 1.0 |
| 7.7114        | 1.0563  | 150  | 5.5788          | 1.0 |
| 6.2512        | 1.4085  | 200  | 5.5017          | 1.0 |
| 6.2512        | 1.7606  | 250  | 5.0778          | 1.0 |
| 5.152         | 2.1127  | 300  | 3.0842          | 1.0 |
| 5.152         | 2.4648  | 350  | 2.9082          | 1.0 |
| 2.9862        | 2.8169  | 400  | 2.9040          | 1.0 |
| 2.9862        | 3.1690  | 450  | 2.9172          | 1.0 |
| 2.9346        | 3.5211  | 500  | 3.0595          | 1.0 |
| 2.9346        | 3.8732  | 550  | 2.8957          | 1.0 |
| 2.9037        | 4.2254  | 600  | 2.9380          | 1.0 |
| 2.9037        | 4.5775  | 650  | 2.8769          | 1.0 |
| 2.8894        | 4.9296  | 700  | 2.9011          | 1.0 |
| 2.8894        | 5.2817  | 750  | 2.8993          | 1.0 |
| 2.8886        | 5.6338  | 800  | 2.8978          | 1.0 |
| 2.8886        | 5.9859  | 850  | 2.8762          | 1.0 |
| 2.8831        | 6.3380  | 900  | 2.8726          | 1.0 |
| 2.8831        | 6.6901  | 950  | 2.8747          | 1.0 |
| 2.8772        | 7.0423  | 1000 | 3.0238          | 1.0 |
| 2.8772        | 7.3944  | 1050 | 2.8764          | 1.0 |
| 2.8913        | 7.7465  | 1100 | 2.8801          | 1.0 |
| 2.8913        | 8.0986  | 1150 | 2.8926          | 1.0 |
| 2.8677        | 8.4507  | 1200 | 2.9241          | 1.0 |
| 2.8677        | 8.8028  | 1250 | 2.9400          | 1.0 |
| 2.8713        | 9.1549  | 1300 | 2.9158          | 1.0 |
| 2.8713        | 9.5070  | 1350 | 2.8834          | 1.0 |
| 2.8702        | 9.8592  | 1400 | 2.8683          | 1.0 |
| 2.8702        | 10.2113 | 1450 | 2.8976          | 1.0 |
| 2.8817        | 10.5634 | 1500 | 2.9263          | 1.0 |
| 2.8817        | 10.9155 | 1550 | 2.8732          | 1.0 |
| 2.8657        | 11.2676 | 1600 | 2.9270          | 1.0 |
| 2.8657        | 11.6197 | 1650 | 2.8860          | 1.0 |
| 2.8618        | 11.9718 | 1700 | 2.8889          | 1.0 |
| 2.8618        | 12.3239 | 1750 | 2.8942          | 1.0 |
| 2.8846        | 12.6761 | 1800 | 2.8856          | 1.0 |
| 2.8846        | 13.0282 | 1850 | 2.9049          | 1.0 |
| 2.8635        | 13.3803 | 1900 | 2.8727          | 1.0 |
| 2.8635        | 13.7324 | 1950 | 2.8900          | 1.0 |
| 2.8634        | 14.0845 | 2000 | 2.9005          | 1.0 |
| 2.8634        | 14.4366 | 2050 | 2.9035          | 1.0 |
| 2.8624        | 14.7887 | 2100 | 2.9030          | 1.0 |
| 2.8624        | 15.1408 | 2150 | 2.8754          | 1.0 |
| 2.8627        | 15.4930 | 2200 | 2.8944          | 1.0 |
| 2.8627        | 15.8451 | 2250 | 2.8651          | 1.0 |
| 2.8595        | 16.1972 | 2300 | 2.9012          | 1.0 |
| 2.8595        | 16.5493 | 2350 | 2.9074          | 1.0 |
| 2.8591        | 16.9014 | 2400 | 2.8764          | 1.0 |
| 2.8591        | 17.2535 | 2450 | 2.8917          | 1.0 |
| 2.8615        | 17.6056 | 2500 | 2.8757          | 1.0 |
| 2.8615        | 17.9577 | 2550 | 2.8945          | 1.0 |
| 2.861         | 18.3099 | 2600 | 2.9263          | 1.0 |
| 2.861         | 18.6620 | 2650 | 2.8842          | 1.0 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3