ser_model
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4615
- Accuracy: 0.8471
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0541 | 1.0 | 162 | 0.9782 | 0.6650 |
0.7858 | 2.0 | 324 | 0.6777 | 0.7624 |
0.5927 | 3.0 | 486 | 0.5659 | 0.8028 |
0.4803 | 4.0 | 648 | 0.5004 | 0.8186 |
0.3951 | 5.0 | 810 | 0.4971 | 0.8175 |
0.3656 | 6.0 | 972 | 0.4670 | 0.8310 |
0.286 | 7.0 | 1134 | 0.4965 | 0.8306 |
0.2879 | 8.0 | 1296 | 0.4620 | 0.8421 |
0.2417 | 9.0 | 1458 | 0.4554 | 0.8460 |
0.2182 | 10.0 | 1620 | 0.4615 | 0.8471 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2
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