metadata
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- ami
metrics:
- wer
model-index:
- name: 6e-5_4000eval
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ami
type: ami
config: ihm
split: None
args: ihm
metrics:
- name: Wer
type: wer
value: 0.2470857142857143
6e-5_4000eval
This model is a fine-tuned version of facebook/wav2vec2-base-960h on the ami dataset. It achieves the following results on the evaluation set:
- Loss: 0.8508
- Wer: 0.2471
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: 6e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 7.5758 | 250 | 5.4590 | 0.9995 |
| 9.3761 | 15.1515 | 500 | 3.7020 | 0.9995 |
| 9.3761 | 22.7273 | 750 | 3.0706 | 0.9995 |
| 3.2176 | 30.3030 | 1000 | 3.0517 | 0.9995 |
| 3.2176 | 37.8788 | 1250 | 1.8920 | 0.7721 |
| 2.0444 | 45.4545 | 1500 | 1.3641 | 0.3488 |
| 2.0444 | 53.0303 | 1750 | 1.1031 | 0.2779 |
| 0.8363 | 60.6061 | 2000 | 1.1269 | 0.2679 |
| 0.8363 | 68.1818 | 2250 | 1.0291 | 0.2656 |
| 0.6824 | 75.7576 | 2500 | 0.9712 | 0.2629 |
| 0.6824 | 83.3333 | 2750 | 0.8902 | 0.2619 |
| 0.5956 | 90.9091 | 3000 | 0.8432 | 0.2441 |
| 0.5956 | 98.4848 | 3250 | 0.8714 | 0.2485 |
| 0.4071 | 106.0606 | 3500 | 0.8222 | 0.2478 |
| 0.4071 | 113.6364 | 3750 | 0.8398 | 0.2501 |
| 0.4479 | 121.2121 | 4000 | 0.8508 | 0.2471 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1