---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-Malayalam
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ml
      split: None
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 0.908768536428111
---

<!-- 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. -->

# wav2vec2-Malayalam

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7479
- Wer: 0.9088

## 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: 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 8.6036        | 1.5748  | 100  | 6.5081          | 1.0    |
| 3.5056        | 3.1496  | 200  | 3.5634          | 1.0    |
| 3.4952        | 4.7244  | 300  | 3.4927          | 1.0    |
| 3.3772        | 6.2992  | 400  | 3.3696          | 1.0    |
| 3.1849        | 7.8740  | 500  | 3.1735          | 1.0    |
| 1.3056        | 9.4488  | 600  | 1.2938          | 1.1167 |
| 0.8162        | 11.0236 | 700  | 0.8301          | 1.0190 |
| 0.6022        | 12.5984 | 800  | 0.7678          | 0.9929 |
| 0.454         | 14.1732 | 900  | 0.7514          | 0.9832 |
| 0.4104        | 15.7480 | 1000 | 0.7168          | 0.9452 |
| 0.3616        | 17.3228 | 1100 | 0.7297          | 0.9571 |
| 0.2951        | 18.8976 | 1200 | 0.6925          | 0.9555 |
| 0.2667        | 20.4724 | 1300 | 0.7254          | 0.9400 |
| 0.2707        | 22.0472 | 1400 | 0.7498          | 0.9101 |
| 0.2263        | 23.6220 | 1500 | 0.7093          | 0.9120 |
| 0.1933        | 25.1969 | 1600 | 0.7396          | 0.9091 |
| 0.2168        | 26.7717 | 1700 | 0.7417          | 0.9046 |
| 0.2112        | 28.3465 | 1800 | 0.7479          | 0.9088 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1.dev0
- Tokenizers 0.19.1