Bajiyo
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w2v-bert-2.0-malayalam_mixeddataset_two.0

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 ---
-library_name: transformers
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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-malayalam_mixeddataset_two.0
+  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-malayalam_mixeddataset_two.0
+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: 0.1425
+- Wer: 0.1451
+## 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: 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.9341        | 0.24  | 300  | 0.4363          | 0.5138 |
+| 0.228         | 0.47  | 600  | 0.3644          | 0.4847 |
+| 0.1828        | 0.71  | 900  | 0.2752          | 0.3807 |
+| 0.1479        | 0.95  | 1200 | 0.2671          | 0.3583 |
+| 0.1213        | 1.19  | 1500 | 0.2291          | 0.2861 |
+| 0.1114        | 1.42  | 1800 | 0.2098          | 0.2754 |
+| 0.1049        | 1.66  | 2100 | 0.2088          | 0.2832 |
+| 0.0962        | 1.9   | 2400 | 0.1789          | 0.2501 |
+| 0.0777        | 2.14  | 2700 | 0.1945          | 0.2371 |
+| 0.0685        | 2.37  | 3000 | 0.1788          | 0.2433 |
+| 0.0663        | 2.61  | 3300 | 0.1707          | 0.2264 |
+| 0.0652        | 2.85  | 3600 | 0.1834          | 0.2227 |
+| 0.0573        | 3.08  | 3900 | 0.1663          | 0.2065 |
+| 0.0445        | 3.32  | 4200 | 0.1479          | 0.1981 |
+| 0.0417        | 3.56  | 4500 | 0.1477          | 0.1779 |
+| 0.0415        | 3.8   | 4800 | 0.1504          | 0.1774 |
+| 0.0368        | 4.03  | 5100 | 0.1407          | 0.1655 |
+| 0.0248        | 4.27  | 5400 | 0.1568          | 0.1672 |
+| 0.0258        | 4.51  | 5700 | 0.1495          | 0.1582 |
+| 0.0227        | 4.74  | 6000 | 0.1460          | 0.1510 |
+| 0.0225        | 4.98  | 6300 | 0.1425          | 0.1451 |
+### Framework versions
+- Transformers 4.39.3
+- Pytorch 2.1.1+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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