wav2vec2-conformer-rel-pos-large-medical-intent-v2
This model is a fine-tuned version of facebook/wav2vec2-conformer-rel-pos-large on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0410
- Accuracy: 0.6170
- Precision: 0.6351
- Recall: 0.6170
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
---|---|---|---|---|---|---|
1.7714 | 1.0 | 82 | 1.7605 | 0.2339 | 0.3198 | 0.2339 |
1.511 | 2.0 | 164 | 1.5148 | 0.4298 | 0.3817 | 0.4298 |
1.1417 | 2.99 | 246 | 1.1530 | 0.5936 | 0.6491 | 0.5936 |
0.8747 | 3.99 | 328 | 1.0410 | 0.6170 | 0.6351 | 0.6170 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for shreyas1104/wav2vec2-conformer-rel-pos-large-medical-intent-v2
Base model
facebook/wav2vec2-conformer-rel-pos-largeEvaluation results
- Accuracy on audiofoldervalidation set self-reported0.617
- Precision on audiofoldervalidation set self-reported0.635
- Recall on audiofoldervalidation set self-reported0.617