metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wav2vec2transformerEMR3
results: []
wav2vec2transformerEMR3
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6589
- Accuracy: 0.7916
- Precision: 0.7918
- Recall: 0.7916
- F1: 0.7896
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.4706 | 1.6420 | 500 | 1.4207 | 0.5409 | 0.5559 | 0.5409 | 0.5180 |
| 0.953 | 3.2841 | 1000 | 0.9292 | 0.7275 | 0.7438 | 0.7275 | 0.7233 |
| 0.7575 | 4.9261 | 1500 | 0.7618 | 0.7616 | 0.7686 | 0.7616 | 0.7610 |
| 0.6084 | 6.5681 | 2000 | 0.7485 | 0.7559 | 0.7658 | 0.7559 | 0.7524 |
| 0.5221 | 8.2102 | 2500 | 0.6990 | 0.7711 | 0.7767 | 0.7711 | 0.7691 |
| 0.431 | 9.8522 | 3000 | 0.6967 | 0.7752 | 0.7796 | 0.7752 | 0.7719 |
| 0.3814 | 11.4943 | 3500 | 0.6523 | 0.7867 | 0.7875 | 0.7867 | 0.7856 |
| 0.3461 | 13.1363 | 4000 | 0.6589 | 0.7916 | 0.7918 | 0.7916 | 0.7896 |
| 0.3405 | 14.7783 | 4500 | 0.6703 | 0.7867 | 0.7878 | 0.7867 | 0.7847 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3