---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec-malayalam-checkpoint
  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. -->

# wav2vec-malayalam-checkpoint

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6457
- Wer: 0.6608

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- num_epochs: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6371        | 10.0  | 100  | 3.5200          | 1.0    |
| 3.3014        | 20.0  | 200  | 3.2092          | 1.0    |
| 1.2997        | 30.0  | 300  | 0.7134          | 0.8847 |
| 0.5078        | 40.0  | 400  | 0.5805          | 0.7841 |
| 0.3795        | 50.0  | 500  | 0.5604          | 0.7289 |
| 0.2809        | 60.0  | 600  | 0.5962          | 0.7055 |
| 0.2381        | 70.0  | 700  | 0.6099          | 0.6938 |
| 0.2046        | 80.0  | 800  | 0.6237          | 0.6862 |
| 0.1826        | 90.0  | 900  | 0.6204          | 0.6755 |
| 0.1627        | 100.0 | 1000 | 0.6335          | 0.6751 |
| 0.1453        | 110.0 | 1100 | 0.6446          | 0.6739 |
| 0.1359        | 120.0 | 1200 | 0.6277          | 0.6648 |
| 0.1274        | 130.0 | 1300 | 0.6356          | 0.6573 |
| 0.1189        | 140.0 | 1400 | 0.6417          | 0.6601 |
| 0.1146        | 150.0 | 1500 | 0.6457          | 0.6608 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.18.3
- Tokenizers 0.10.3