metadata
license: apache-2.0
base_model: facebook/wav2vec2-conformer-rel-pos-large
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
- precision
- recall
model-index:
- name: wav2vec2-conformer-rel-pos-large-medical-intent-v2
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6169590643274854
- name: Precision
type: precision
value: 0.6350528050296339
- name: Recall
type: recall
value: 0.6169590643274854
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