---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: wav2vec2-base_phoneme-timit_english_timit-4k_001
  results: []
language:
- en
metrics:
- wer
library_name: transformers
pipeline_tag: automatic-speech-recognition
---

<!-- 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. -->

# wav2vec2-base_phoneme-timit_english_timit-4k_001

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the timit dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6361
- Per: 0.1195

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.2193        | 3.46  | 1000  | 3.5945          | 0.9617 |
| 1.5174        | 6.92  | 2000  | 0.5574          | 0.1665 |
| 0.5246        | 10.38 | 3000  | 0.4228          | 0.1503 |
| 0.3915        | 13.84 | 4000  | 0.4276          | 0.1512 |
| 0.3293        | 17.3  | 5000  | 0.4656          | 0.1517 |
| 0.2757        | 20.76 | 6000  | 0.4719          | 0.1486 |
| 0.209         | 24.22 | 7000  | 0.5314          | 0.1478 |
| 0.1589        | 27.68 | 8000  | 0.6102          | 0.1484 |
| 0.1207        | 31.14 | 9000  | 0.6449          | 0.1484 |
| 0.0951        | 34.6  | 10000 | 0.6579          | 0.1471 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.13.3