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

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: 0.8941
- Slot P: 0.0093
- Slot R: 0.0199
- Slot F1: 0.0127
- Slot Exact Match: 0.0679
- Intent Acc: 0.8756

## 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: 10
- 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   | 2.2457          | 0.0123 | 0.0064 | 0.0085  | 0.3665           | 0.7201     |
| 10.82         | 2.0   | 90   | 1.1090          | 0.0111 | 0.0182 | 0.0138  | 0.1756           | 0.8598     |
| 2.7961        | 3.0   | 135  | 0.9549          | 0.0097 | 0.0176 | 0.0125  | 0.1604           | 0.8647     |
| 1.7004        | 4.0   | 180  | 0.9027          | 0.0098 | 0.0193 | 0.0130  | 0.1215           | 0.8726     |
| 1.2198        | 5.0   | 225  | 0.8941          | 0.0093 | 0.0199 | 0.0127  | 0.0679           | 0.8756     |


### Framework versions

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