---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-MCV15
  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. -->

# wav2vec2-xls-r-300m-MCV15

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: 1.0523
- Wer: 0.7437
- Cer: 0.2712

## 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: 24
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 12.5819       | 4.5   | 250  | 4.5566          | 1.0    | 1.0000 |
| 3.4789        | 9.01  | 500  | 3.1356          | 1.0    | 1.0000 |
| 3.0456        | 13.51 | 750  | 2.9915          | 1.0    | 1.0000 |
| 2.7595        | 18.02 | 1000 | 2.2266          | 0.9648 | 0.6214 |
| 1.9067        | 22.52 | 1250 | 1.4719          | 0.8477 | 0.3298 |
| 1.3924        | 27.03 | 1500 | 1.2345          | 0.8086 | 0.2978 |
| 1.168         | 31.53 | 1750 | 1.1614          | 0.7843 | 0.2893 |
| 1.0616        | 36.04 | 2000 | 1.1134          | 0.7690 | 0.2824 |
| 0.9895        | 40.54 | 2250 | 1.0685          | 0.7489 | 0.2749 |
| 0.9316        | 45.05 | 2500 | 1.0537          | 0.7451 | 0.2715 |
| 0.9192        | 49.55 | 2750 | 1.0523          | 0.7437 | 0.2712 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0