|
--- |
|
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 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jadorantes2-utep/%3Cmy-amazing-projecttokenizer6e-5eval4000%3E/runs/c41b6hhn) |
|
# 6e-5_4000eval |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/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 |
|
|
