---
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: 1.1155
- Wer: 0.6060
- Cer: 0.2242

## 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: 8e-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: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 9.8843        | 4.5   | 250  | 3.3243          | 1.0    | 1.0000 |
| 3.066         | 9.01  | 500  | 2.8141          | 1.0    | 1.0000 |
| 1.8006        | 13.51 | 750  | 1.1647          | 0.7936 | 0.3028 |
| 0.8925        | 18.02 | 1000 | 1.0696          | 0.7174 | 0.2679 |
| 0.6306        | 22.52 | 1250 | 1.0330          | 0.6792 | 0.2509 |
| 0.512         | 27.03 | 1500 | 0.9988          | 0.6560 | 0.2405 |
| 0.4275        | 31.53 | 1750 | 1.0428          | 0.6345 | 0.2332 |
| 0.3837        | 36.04 | 2000 | 1.0555          | 0.6267 | 0.2315 |
| 0.3481        | 40.54 | 2250 | 1.1165          | 0.6231 | 0.2312 |
| 0.3081        | 45.05 | 2500 | 1.0772          | 0.6142 | 0.2255 |
| 0.2906        | 49.55 | 2750 | 1.1146          | 0.6085 | 0.2267 |
| 0.2923        | 54.05 | 3000 | 1.1030          | 0.6058 | 0.2228 |
| 0.259         | 58.56 | 3250 | 1.1155          | 0.6060 | 0.2242 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0