---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-Tamil-large
  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. -->

# wav2vec2-base-Tamil-large

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3015
- Wer: 0.3470
- Cer: 0.0610

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 5.2014        | 2.2472  | 300  | 3.2558          | 1.0    | 1.0    |
| 1.1765        | 4.4944  | 600  | 0.5245          | 0.7139 | 0.1482 |
| 0.4765        | 6.7416  | 900  | 0.4191          | 0.6080 | 0.1133 |
| 0.33          | 8.9888  | 1200 | 0.3494          | 0.4983 | 0.0910 |
| 0.2488        | 11.2360 | 1500 | 0.3163          | 0.4470 | 0.0811 |
| 0.1951        | 13.4831 | 1800 | 0.3326          | 0.4179 | 0.0748 |
| 0.1586        | 15.7303 | 2100 | 0.3135          | 0.3924 | 0.0702 |
| 0.1308        | 17.9775 | 2400 | 0.3070          | 0.3798 | 0.0668 |
| 0.1111        | 20.2247 | 2700 | 0.2999          | 0.3618 | 0.0635 |
| 0.0996        | 22.4719 | 3000 | 0.3015          | 0.3470 | 0.0610 |


### Framework versions

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