metadata
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-base-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: 0.33567800752279153
wav2vec2-base-ami-fine-tuned
This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the EDINBURGHCSTR/AMI - IHM dataset. It achieves the following results on the evaluation set:
- Loss: 0.5988
- Wer: 0.3357
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: 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: 500
- num_epochs: 2.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0732 | 0.1565 | 1000 | 1.1351 | 0.6738 |
| 1.4052 | 0.3131 | 2000 | 0.7311 | 0.4083 |
| 0.8798 | 0.4696 | 3000 | 0.5889 | 0.3604 |
| 0.4789 | 0.6262 | 4000 | 0.5681 | 0.3521 |
| 0.8011 | 0.7827 | 5000 | 0.5288 | 0.3382 |
| 1.4331 | 0.9393 | 6000 | 0.5386 | 0.3280 |
| 0.2201 | 1.0958 | 7000 | 0.5154 | 0.3198 |
| 0.1934 | 1.2523 | 8000 | 0.4895 | 0.3131 |
| 0.2713 | 1.4089 | 9000 | 0.4809 | 0.3065 |
| 0.1388 | 1.5654 | 10000 | 0.4984 | 0.3061 |
| 0.4085 | 1.7220 | 11000 | 0.4842 | 0.3082 |
| 0.3529 | 1.8785 | 12000 | 0.5417 | 0.3198 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0a0+gitcd033a1
- Datasets 2.19.1
- Tokenizers 0.19.1