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---
library_name: transformers
license: apache-2.0
base_model: uitnlp/CafeBERT
tags:
- generated_from_trainer
model-index:
- name: CafeBERT_massive_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CafeBERT_massive_v2
This model is a fine-tuned version of [uitnlp/CafeBERT](https://huggingface.co/uitnlp/CafeBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9485
- Slot P: 0.0090
- Slot R: 0.0199
- Slot F1: 0.0124
- Slot Exact Match: 0.0418
- Intent Acc: 0.8647
## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Slot P | Slot R | Slot F1 | Slot Exact Match | Intent Acc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:----------------:|:----------:|
| No log | 1.0 | 45 | 4.1897 | 0.0 | 0.0 | 0.0 | 0.4088 | 0.3478 |
| 12.6262 | 2.0 | 90 | 1.3454 | 0.0090 | 0.0129 | 0.0106 | 0.1943 | 0.8406 |
| 4.1265 | 3.0 | 135 | 1.0228 | 0.0102 | 0.0193 | 0.0134 | 0.1181 | 0.8564 |
| 1.987 | 4.0 | 180 | 0.9293 | 0.0100 | 0.0188 | 0.0130 | 0.1313 | 0.8692 |
| 1.382 | 5.0 | 225 | 0.9144 | 0.0096 | 0.0205 | 0.0131 | 0.0644 | 0.8706 |
| 1.0689 | 6.0 | 270 | 0.9485 | 0.0090 | 0.0199 | 0.0124 | 0.0418 | 0.8647 |
### Framework versions
- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4
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