---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-Tamil-large-xlsr53
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-Tamil-large-xlsr53

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2781
- Wer: 0.3110
- Cer: 0.0517

## 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: 0.0003
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 5.904         | 2.2472  | 300  | 3.1297          | 1.0    | 0.9873 |
| 0.9535        | 4.4944  | 600  | 0.3668          | 0.5619 | 0.1031 |
| 0.2594        | 6.7416  | 900  | 0.2991          | 0.4758 | 0.0811 |
| 0.1648        | 8.9888  | 1200 | 0.2692          | 0.4060 | 0.0670 |
| 0.1146        | 11.2360 | 1500 | 0.2712          | 0.3747 | 0.0617 |
| 0.0904        | 13.4831 | 1800 | 0.2722          | 0.3488 | 0.0577 |
| 0.0734        | 15.7303 | 2100 | 0.2682          | 0.3317 | 0.0568 |
| 0.0597        | 17.9775 | 2400 | 0.2778          | 0.3263 | 0.0548 |
| 0.0553        | 20.2247 | 2700 | 0.2740          | 0.3153 | 0.0526 |
| 0.0466        | 22.4719 | 3000 | 0.2781          | 0.3110 | 0.0517 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 1.18.3
- Tokenizers 0.19.1