File size: 3,365 Bytes
53a8f30 837c0bf 53a8f30 837c0bf 53a8f30 | 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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | ---
base_model: mascIT/bert-tiny-ita
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: test_trainer
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. -->
# test_trainer
This model is a fine-tuned version of [mascIT/bert-tiny-ita](https://huggingface.co/mascIT/bert-tiny-ita) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5112
- Accuracy: 0.9083
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 32
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 60 | 2.0721 | 0.425 |
| No log | 2.0 | 120 | 1.9418 | 0.4667 |
| No log | 3.0 | 180 | 1.8074 | 0.5833 |
| No log | 4.0 | 240 | 1.6822 | 0.6333 |
| No log | 5.0 | 300 | 1.5631 | 0.7 |
| No log | 6.0 | 360 | 1.4501 | 0.7333 |
| No log | 7.0 | 420 | 1.3494 | 0.7583 |
| No log | 8.0 | 480 | 1.2584 | 0.8167 |
| 1.6858 | 9.0 | 540 | 1.1861 | 0.8 |
| 1.6858 | 10.0 | 600 | 1.1065 | 0.825 |
| 1.6858 | 11.0 | 660 | 1.0426 | 0.8333 |
| 1.6858 | 12.0 | 720 | 0.9774 | 0.8333 |
| 1.6858 | 13.0 | 780 | 0.9263 | 0.825 |
| 1.6858 | 14.0 | 840 | 0.8681 | 0.8417 |
| 1.6858 | 15.0 | 900 | 0.8267 | 0.85 |
| 1.6858 | 16.0 | 960 | 0.7704 | 0.8583 |
| 0.8889 | 17.0 | 1020 | 0.7324 | 0.875 |
| 0.8889 | 18.0 | 1080 | 0.7094 | 0.8583 |
| 0.8889 | 19.0 | 1140 | 0.6825 | 0.8583 |
| 0.8889 | 20.0 | 1200 | 0.6484 | 0.8833 |
| 0.8889 | 21.0 | 1260 | 0.6230 | 0.8833 |
| 0.8889 | 22.0 | 1320 | 0.6056 | 0.875 |
| 0.8889 | 23.0 | 1380 | 0.5884 | 0.8833 |
| 0.8889 | 24.0 | 1440 | 0.5629 | 0.9 |
| 0.5022 | 25.0 | 1500 | 0.5537 | 0.8917 |
| 0.5022 | 26.0 | 1560 | 0.5485 | 0.8917 |
| 0.5022 | 27.0 | 1620 | 0.5411 | 0.8833 |
| 0.5022 | 28.0 | 1680 | 0.5254 | 0.9083 |
| 0.5022 | 29.0 | 1740 | 0.5198 | 0.9083 |
| 0.5022 | 30.0 | 1800 | 0.5157 | 0.9083 |
| 0.5022 | 31.0 | 1860 | 0.5107 | 0.9083 |
| 0.5022 | 32.0 | 1920 | 0.5112 | 0.9083 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.3.1.post300
- Datasets 3.2.0
- Tokenizers 0.21.0
|