model_output
This model is a fine-tuned version of beomi/kcbert-base on the unsmile_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.1302
- Lrap: 0.8800
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Lrap |
---|---|---|---|---|
No log | 1.0 | 235 | 0.1502 | 0.8535 |
No log | 2.0 | 470 | 0.1297 | 0.8706 |
0.1747 | 3.0 | 705 | 0.1229 | 0.8803 |
0.1747 | 4.0 | 940 | 0.1288 | 0.8802 |
0.0784 | 5.0 | 1175 | 0.1302 | 0.8800 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Downloads last month
- 1
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for audgns/model_output
Base model
beomi/kcbert-base