pytorch tensorboard wav2vec2 automatic-speech-recognition dataset:librispeech_asr transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: wav2vec2-large-xls-r-300m-en-colab
  results: []
---

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# wav2vec2-large-xls-r-300m-en-colab

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the librispeech_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7541
- Wer: 1.0
- Cer: 0.9877

## 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: 0.001
- 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: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:---:|:------:|
| No log        | 1.94  | 33   | 2.9905          | 1.0 | 1.0    |
| No log        | 3.88  | 66   | 2.9023          | 1.0 | 1.0    |
| No log        | 5.82  | 99   | 2.8788          | 1.0 | 1.0    |
| 3.7488        | 7.76  | 132  | 2.8624          | 1.0 | 1.0    |
| 3.7488        | 9.71  | 165  | 2.7541          | 1.0 | 0.9877 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cpu
- Datasets 1.18.3
- Tokenizers 0.12.1
