---
library_name: transformers
license: apache-2.0
base_model: uitnlp/CafeBERT
tags:
- generated_from_trainer
model-index:
- name: CafeBERT_massive_v3
  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_v3

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: 5.2297
- Slot P: 0.7256
- Slot R: 0.7801
- Slot F1: 0.7519
- Slot Exact Match: 0.7260
- Intent Acc: 0.8633

## 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   | 16.4744         | 0.2572 | 0.0801 | 0.1222  | 0.3114           | 0.0930     |
| 72.336        | 2.0   | 90   | 6.6272          | 0.5583 | 0.6075 | 0.5818  | 0.5268           | 0.6021     |
| 20.704        | 3.0   | 135  | 4.4083          | 0.6449 | 0.7338 | 0.6865  | 0.6596           | 0.7885     |
| 9.4202        | 4.0   | 180  | 3.7185          | 0.6867 | 0.7493 | 0.7166  | 0.6926           | 0.8367     |
| 6.3529        | 5.0   | 225  | 3.6662          | 0.7024 | 0.7726 | 0.7358  | 0.7083           | 0.8647     |
| 4.7787        | 6.0   | 270  | 3.8379          | 0.7102 | 0.7657 | 0.7369  | 0.7122           | 0.8667     |
| 3.6929        | 7.0   | 315  | 3.7687          | 0.7152 | 0.7796 | 0.7460  | 0.7191           | 0.8652     |
| 2.9663        | 8.0   | 360  | 4.1024          | 0.7037 | 0.7905 | 0.7446  | 0.7186           | 0.8677     |
| 2.4189        | 9.0   | 405  | 4.2478          | 0.7177 | 0.7856 | 0.7501  | 0.7206           | 0.8692     |
| 1.9492        | 10.0  | 450  | 4.4022          | 0.7179 | 0.7801 | 0.7477  | 0.7275           | 0.8697     |
| 1.9492        | 11.0  | 495  | 4.6437          | 0.7095 | 0.7751 | 0.7408  | 0.7122           | 0.8706     |
| 1.5099        | 12.0  | 540  | 4.7049          | 0.7223 | 0.7881 | 0.7537  | 0.7290           | 0.8706     |
| 1.2818        | 13.0  | 585  | 4.9417          | 0.7189 | 0.7811 | 0.7487  | 0.7245           | 0.8677     |
| 1.0546        | 14.0  | 630  | 5.0501          | 0.7188 | 0.7781 | 0.7473  | 0.7226           | 0.8667     |
| 0.8641        | 15.0  | 675  | 5.2297          | 0.7256 | 0.7801 | 0.7519  | 0.7260           | 0.8633     |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4