|
--- |
|
license: cc-by-sa-4.0 |
|
base_model: aiknowyou/it-emotion-analyzer |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: it-emotion-analyzer_finetuned_pro_multilbel_emit |
|
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. --> |
|
|
|
# it-emotion-analyzer_finetuned_pro_multilbel_emit |
|
|
|
This model is a fine-tuned version of [aiknowyou/it-emotion-analyzer](https://huggingface.co/aiknowyou/it-emotion-analyzer) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2714 |
|
- F1: 0.4804 |
|
- Roc Auc: 0.6939 |
|
- Accuracy: 0.3110 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:| |
|
| 0.2712 | 1.0 | 1037 | 0.2740 | 0.3755 | 0.6250 | 0.2680 | |
|
| 0.2238 | 2.0 | 2074 | 0.2703 | 0.4161 | 0.6504 | 0.2749 | |
|
| 0.1743 | 3.0 | 3111 | 0.2714 | 0.4804 | 0.6939 | 0.3110 | |
|
| 0.143 | 4.0 | 4148 | 0.2838 | 0.4632 | 0.6811 | 0.2887 | |
|
| 0.1089 | 5.0 | 5185 | 0.2971 | 0.4756 | 0.6897 | 0.3041 | |
|
| 0.0874 | 6.0 | 6222 | 0.3242 | 0.4718 | 0.6965 | 0.2887 | |
|
| 0.0726 | 7.0 | 7259 | 0.3414 | 0.4798 | 0.7003 | 0.3076 | |
|
| 0.0565 | 8.0 | 8296 | 0.3538 | 0.4690 | 0.6897 | 0.2973 | |
|
| 0.0501 | 9.0 | 9333 | 0.3712 | 0.4696 | 0.6959 | 0.2938 | |
|
| 0.0426 | 10.0 | 10370 | 0.3692 | 0.4702 | 0.6922 | 0.2904 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.1 |
|
- Pytorch 2.3.0+cu118 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|