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w2v-bert-Tamil-large

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 ---
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-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. -->
+# w2v-bert-Tamil-large
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1815
+- Wer: 0.2176
+- Cer: 0.0328
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 2.0779        | 0.75  | 300  | 0.4934          | 0.6338 | 0.1189 |
+| 0.3653        | 1.5   | 600  | 0.4045          | 0.5424 | 0.0975 |
+| 0.2632        | 2.25  | 900  | 0.3148          | 0.4421 | 0.0723 |
+| 0.2084        | 3.0   | 1200 | 0.2297          | 0.3499 | 0.0576 |
+| 0.1359        | 3.75  | 1500 | 0.2042          | 0.3060 | 0.0464 |
+| 0.1049        | 4.5   | 1800 | 0.1939          | 0.2836 | 0.0446 |
+| 0.0823        | 5.25  | 2100 | 0.1827          | 0.2504 | 0.0382 |
+| 0.0561        | 6.0   | 2400 | 0.1731          | 0.2419 | 0.0368 |
+| 0.0352        | 6.75  | 2700 | 0.1802          | 0.2275 | 0.0335 |
+| 0.0224        | 7.5   | 3000 | 0.1815          | 0.2176 | 0.0328 |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1