File size: 2,247 Bytes
baf54c6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
base_model: Musixmatch/umberto-commoncrawl-cased-v1
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: irony_classification_ita_base
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. -->
# irony_classification_ita_base
This model is a fine-tuned version of [Musixmatch/umberto-commoncrawl-cased-v1](https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9229
- F1: 0.7035
- Roc Auc: 0.7635
- Accuracy: 0.6124
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log | 1.0 | 485 | 0.4856 | 0.6741 | 0.7414 | 0.5845 |
| 0.5349 | 2.0 | 970 | 0.5023 | 0.6423 | 0.7255 | 0.6175 |
| 0.4217 | 3.0 | 1455 | 0.5592 | 0.6433 | 0.7265 | 0.6113 |
| 0.3188 | 4.0 | 1940 | 0.6664 | 0.6549 | 0.7322 | 0.6134 |
| 0.2303 | 5.0 | 2425 | 0.8518 | 0.6122 | 0.7071 | 0.6062 |
| 0.1588 | 6.0 | 2910 | 0.9229 | 0.7035 | 0.7635 | 0.6124 |
| 0.1123 | 7.0 | 3395 | 0.9859 | 0.6677 | 0.7406 | 0.6082 |
| 0.0761 | 8.0 | 3880 | 1.0392 | 0.6875 | 0.7536 | 0.6206 |
| 0.0524 | 9.0 | 4365 | 1.0789 | 0.6846 | 0.7515 | 0.6206 |
| 0.0461 | 10.0 | 4850 | 1.0948 | 0.6947 | 0.7583 | 0.6206 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
|