---
license: apache-2.0
base_model: facebook/wav2vec2-large-lv60
tags:
- automatic-speech-recognition
- edinburghcstr/ami
- generated_from_trainer
datasets:
- ami
metrics:
- wer
model-index:
- name: wav2vec2-large-ami-fine-tuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: EDINBURGHCSTR/AMI - IHM
      type: ami
      config: ihm
      split: None
      args: 'Config: ihm, Training split: train, Eval split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 0.9958454640117305
---

<!-- 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-large-ami-fine-tuned

This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the EDINBURGHCSTR/AMI - IHM dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9555
- Wer: 0.9958

## 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: 0.00014
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 1.5455        | 0.1565 | 1000  | 1.3698          | 0.8373 |
| 1.3019        | 0.3131 | 2000  | 0.7275          | 0.4146 |
| 0.9922        | 0.4696 | 3000  | 0.6047          | 0.3663 |
| 0.5129        | 0.6262 | 4000  | 0.5773          | 0.3658 |
| 0.85          | 0.7827 | 5000  | 0.5387          | 0.3538 |
| 1.4588        | 0.9393 | 6000  | 0.5581          | 0.3326 |
| 0.2646        | 1.0958 | 7000  | 0.5216          | 0.3294 |
| 0.1923        | 1.2523 | 8000  | 0.4975          | 0.3159 |
| 0.2897        | 1.4089 | 9000  | 0.4757          | 0.3066 |
| 0.1536        | 1.5654 | 10000 | 0.4784          | 0.3066 |
| 0.3964        | 1.7220 | 11000 | 0.4899          | 0.3097 |
| 1.1026        | 1.8785 | 12000 | 0.9830          | 0.8711 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0a0+gitcd033a1
- Datasets 2.19.1
- Tokenizers 0.19.1