End of training
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README.md
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/krishnan-aravind/huggingface/runs/
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# malayalam_combined_
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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| 0.3823 | 5.0782 | 12500 | 0.5002 | 0.4637 |
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| 0.3893 | 5.2813 | 13000 | 0.4793 | 0.4666 |
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| 0.3789 | 5.4845 | 13500 | 0.4742 | 0.4564 |
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| 0.3718 | 5.6876 | 14000 | 0.4731 | 0.4606 |
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| 0.3813 | 5.8907 | 14500 | 0.4609 | 0.4639 |
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| 0.3498 | 6.0938 | 15000 | 0.4645 | 0.4532 |
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| 0.348 | 6.2970 | 15500 | 0.4662 | 0.4508 |
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| 0.3263 | 6.5001 | 16000 | 0.4635 | 0.4493 |
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| 0.3404 | 6.7032 | 16500 | 0.4522 | 0.4399 |
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| 0.3352 | 6.9064 | 17000 | 0.4439 | 0.4459 |
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| 0.3192 | 7.1095 | 17500 | 0.4490 | 0.4486 |
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| 0.3035 | 7.3126 | 18000 | 0.4474 | 0.4381 |
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| 0.3175 | 7.5157 | 18500 | 0.4431 | 0.4374 |
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| 0.3161 | 7.7189 | 19000 | 0.4458 | 0.4344 |
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| 0.3244 | 7.9220 | 19500 | 0.4384 | 0.4377 |
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| 0.2795 | 8.1251 | 20000 | 0.4444 | 0.4326 |
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| 0.2975 | 8.3283 | 20500 | 0.4403 | 0.4307 |
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| 0.2854 | 8.5314 | 21000 | 0.4352 | 0.4278 |
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| 0.2856 | 8.7345 | 21500 | 0.4344 | 0.4288 |
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| 0.2764 | 8.9376 | 22000 | 0.4356 | 0.4239 |
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| 0.2546 | 9.1408 | 22500 | 0.4426 | 0.4229 |
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| 0.2703 | 9.3439 | 23000 | 0.4336 | 0.4237 |
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| 0.2438 | 9.5470 | 23500 | 0.4358 | 0.4218 |
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| 0.2612 | 9.7502 | 24000 | 0.4337 | 0.4195 |
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| 0.2698 | 9.9533 | 24500 | 0.4324 | 0.4182 |
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### Framework versions
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/krishnan-aravind/huggingface/runs/e0c2wxc6)
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# malayalam_combined_
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.5153
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- Wer: 0.5077
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- num_epochs: 25
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:-----:|:---------------:|:------:|
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| 0.8243 | 0.2031 | 500 | 0.8413 | 0.6658 |
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| 0.7336 | 0.4063 | 1000 | 0.7351 | 0.6251 |
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| 0.6824 | 0.6094 | 1500 | 0.6786 | 0.5956 |
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| 0.6489 | 0.8125 | 2000 | 0.6836 | 0.6075 |
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| 0.585 | 1.0156 | 2500 | 0.6295 | 0.5864 |
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| 0.5917 | 1.2188 | 3000 | 0.6166 | 0.5579 |
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| 0.56 | 1.4219 | 3500 | 0.6006 | 0.5646 |
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| 0.5736 | 1.6250 | 4000 | 0.6268 | 0.5643 |
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| 0.5821 | 1.8282 | 4500 | 0.6216 | 0.5786 |
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| 0.5505 | 2.0313 | 5000 | 0.5705 | 0.5379 |
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| 0.5065 | 2.2344 | 5500 | 0.5864 | 0.5460 |
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| 0.5004 | 2.4375 | 6000 | 0.5555 | 0.5259 |
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| 0.5327 | 2.6407 | 6500 | 0.5539 | 0.5255 |
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| 0.5148 | 2.8438 | 7000 | 0.5584 | 0.5457 |
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| 0.4751 | 3.0469 | 7500 | 0.5389 | 0.5208 |
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| 0.4779 | 3.2501 | 8000 | 0.5284 | 0.5102 |
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| 0.4874 | 3.4532 | 8500 | 0.5300 | 0.5084 |
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| 0.4955 | 3.6563 | 9000 | 0.5248 | 0.5125 |
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| 0.4961 | 3.8594 | 9500 | 0.5116 | 0.5061 |
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| 0.4449 | 4.0626 | 10000 | 0.5257 | 0.5122 |
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| 0.48 | 4.2657 | 10500 | 0.5254 | 0.5046 |
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| 0.4513 | 4.4688 | 11000 | 0.5364 | 0.5232 |
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| 0.4698 | 4.6719 | 11500 | 0.5293 | 0.5106 |
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| 0.4674 | 4.8751 | 12000 | 0.5153 | 0.5077 |
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### Framework versions
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 2423199960
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version https://git-lfs.github.com/spec/v1
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oid sha256:1c80e7d2b3bcd80794a838ea7a69d53e5e32c247cb6bcf6c9e61c671143203e8
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size 2423199960
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