---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-malayalam_mixeddataset_thre
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-2.0-malayalam_mixeddataset_thre

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: 0.1604
- Wer: 0.1244

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.1974        | 0.47  | 600   | 0.3732          | 0.4971 |
| 0.1677        | 0.95  | 1200  | 0.2552          | 0.3411 |
| 0.1229        | 1.42  | 1800  | 0.2184          | 0.3123 |
| 0.1041        | 1.9   | 2400  | 0.2044          | 0.2921 |
| 0.0825        | 2.37  | 3000  | 0.2150          | 0.2667 |
| 0.0756        | 2.85  | 3600  | 0.1882          | 0.2361 |
| 0.0627        | 3.32  | 4200  | 0.1735          | 0.2493 |
| 0.0557        | 3.8   | 4800  | 0.1653          | 0.2117 |
| 0.0454        | 4.27  | 5400  | 0.1669          | 0.1891 |
| 0.0394        | 4.74  | 6000  | 0.1610          | 0.1903 |
| 0.0363        | 5.22  | 6600  | 0.1654          | 0.1699 |
| 0.0278        | 5.69  | 7200  | 0.1465          | 0.1640 |
| 0.025         | 6.17  | 7800  | 0.1503          | 0.1617 |
| 0.0198        | 6.64  | 8400  | 0.1429          | 0.1466 |
| 0.0174        | 7.12  | 9000  | 0.1440          | 0.1453 |
| 0.013         | 7.59  | 9600  | 0.1496          | 0.1433 |
| 0.0125        | 8.07  | 10200 | 0.1465          | 0.1274 |
| 0.0076        | 8.54  | 10800 | 0.1479          | 0.1349 |
| 0.0076        | 9.02  | 11400 | 0.1521          | 0.1229 |
| 0.0041        | 9.49  | 12000 | 0.1600          | 0.1291 |
| 0.0038        | 9.96  | 12600 | 0.1604          | 0.1244 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1