pytorch tensorboard wav2vec2 automatic-speech-recognition en transformers ami generated_from_trainer license:apache-2.0 model-index
---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- ami
- generated_from_trainer
model-index:
- name: wav2vec2-large-lv60-ami_multi-tune_dropout_0.0001_16
  results: []
---

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# wav2vec2-large-lv60-ami_multi-tune_dropout_0.0001_16

This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the AMI-IHM dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5093
- Wer: 0.4409

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.3734        | 1.72  | 1000 | 1.8809          | 0.7894 |
| 1.4869        | 3.45  | 2000 | 1.3396          | 0.4307 |
| 1.3855        | 5.17  | 3000 | 1.2935          | 0.4099 |
| 1.3272        | 6.9   | 4000 | 1.2572          | 0.4044 |
| 1.3057        | 8.62  | 5000 | 1.2504          | 0.3975 |


### Framework versions

- Transformers 4.12.0.dev0
- Pytorch 1.9.1
- Datasets 1.12.2.dev0
- Tokenizers 0.10.3
