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---
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
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