---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-malayalam-colab-CV17.0
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ml
      split: test
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 1.0029013539651837
---

<!-- 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-xls-r-300m-malayalam-colab-CV17.0

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6154
- Wer: 1.0029
- Cer: 0.4254

## 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: 3e-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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 15.7515       | 3.1496  | 200  | 7.2856          | 1.0    | 1.0    |
| 5.2078        | 6.2992  | 400  | 3.9581          | 1.0    | 1.0    |
| 3.6268        | 9.4488  | 600  | 3.4876          | 1.0    | 0.9923 |
| 3.4082        | 12.5984 | 800  | 3.3891          | 1.0    | 0.9906 |
| 3.3259        | 15.7480 | 1000 | 3.3171          | 0.9984 | 0.9415 |
| 3.0224        | 18.8976 | 1200 | 2.6551          | 1.0    | 0.7845 |
| 2.1063        | 22.0472 | 1400 | 1.9206          | 0.9942 | 0.4722 |
| 1.564         | 25.1969 | 1600 | 1.6999          | 0.9916 | 0.4298 |
| 1.3323        | 28.3465 | 1800 | 1.6358          | 0.9990 | 0.4264 |
| 1.2413        | 31.4961 | 2000 | 1.6154          | 1.0029 | 0.4254 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1