---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-tamil-gpu-custom_v10
  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. -->

# w2v-bert-2.0-tamil-gpu-custom_v10

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.4032

## 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: 4.43567e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.4046        | 0.24  | 300  | inf             | 0.3596 |
| 0.5204        | 0.49  | 600  | inf             | 0.3451 |
| 0.4297        | 0.73  | 900  | inf             | 0.3272 |
| 0.3891        | 0.97  | 1200 | inf             | 0.3477 |
| 0.6568        | 1.22  | 1500 | inf             | 0.3937 |
| 0.862         | 1.46  | 1800 | inf             | 0.4033 |
| 0.9171        | 1.71  | 2100 | inf             | 0.4032 |
| 0.9643        | 1.95  | 2400 | inf             | 0.4032 |
| 0.9568        | 2.19  | 2700 | inf             | 0.4032 |
| 0.8953        | 2.44  | 3000 | inf             | 0.4032 |
| 0.9372        | 2.68  | 3300 | inf             | 0.4032 |
| 0.9671        | 2.92  | 3600 | inf             | 0.4032 |
| 0.9527        | 3.17  | 3900 | inf             | 0.4032 |
| 0.8851        | 3.41  | 4200 | inf             | 0.4032 |
| 0.8781        | 3.65  | 4500 | inf             | 0.4032 |
| 0.8971        | 3.9   | 4800 | inf             | 0.4032 |
| 0.8623        | 4.14  | 5100 | inf             | 0.4032 |
| 0.9137        | 4.38  | 5400 | inf             | 0.4032 |
| 0.8969        | 4.63  | 5700 | inf             | 0.4032 |
| 0.8769        | 4.87  | 6000 | inf             | 0.4032 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2