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---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: malayalam_combined_Conversation
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. -->
[<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/pvq9zsxy)
# malayalam_combined_Conversation
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: 0.9570
- Wer: 0.6223
## 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: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.3673 | 0.6177 | 500 | 1.3771 | 0.7996 |
| 1.1485 | 1.2353 | 1000 | 1.2069 | 0.7644 |
| 1.0712 | 1.8530 | 1500 | 1.1157 | 0.7296 |
| 1.0101 | 2.4707 | 2000 | 1.0969 | 0.7344 |
| 0.9326 | 3.0883 | 2500 | 1.0566 | 0.6889 |
| 0.8723 | 3.7060 | 3000 | 1.0339 | 0.6861 |
| 0.8198 | 4.3237 | 3500 | 1.0028 | 0.6830 |
| 0.8092 | 4.9413 | 4000 | 1.0108 | 0.6681 |
| 0.7574 | 5.5590 | 4500 | 1.0049 | 0.6676 |
| 0.7027 | 6.1767 | 5000 | 0.9725 | 0.6660 |
| 0.6981 | 6.7943 | 5500 | 0.9649 | 0.6653 |
| 0.6684 | 7.4120 | 6000 | 0.9500 | 0.6393 |
| 0.6295 | 8.0296 | 6500 | 0.9535 | 0.6364 |
| 0.5947 | 8.6473 | 7000 | 0.9522 | 0.6338 |
| 0.5483 | 9.2650 | 7500 | 0.9821 | 0.6262 |
| 0.5437 | 9.8826 | 8000 | 0.9570 | 0.6223 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 1.14.0a0+44dac51
- Datasets 2.16.1
- Tokenizers 0.19.1
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