File size: 1,952 Bytes
c1ad50a 6bfb409 c1ad50a 6bfb409 00240d1 6bfb409 c1ad50a 00240d1 c1ad50a 6bfb409 00240d1 6bfb409 c1ad50a |
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 |
---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: deberta-v3-ft-news-sentiment-analisys
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. -->
# deberta-v3-ft-news-sentiment-analisys
This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1107
- Precision: 0.9780
- Recall: 0.9780
- Accuracy: 0.9780
- F1: 0.9780
## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log | 1.0 | 64 | 0.4196 | 0.7885 | 0.7885 | 0.7885 | 0.7885 |
| No log | 2.0 | 128 | 0.2166 | 0.9515 | 0.9515 | 0.9515 | 0.9515 |
| No log | 3.0 | 192 | 0.1431 | 0.9604 | 0.9604 | 0.9604 | 0.9604 |
| No log | 4.0 | 256 | 0.1107 | 0.9780 | 0.9780 | 0.9780 | 0.9780 |
| No log | 5.0 | 320 | 0.1292 | 0.9692 | 0.9692 | 0.9692 | 0.9692 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|