File size: 3,787 Bytes
65f4d3d |
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 93 94 95 96 97 |
---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: INT03
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. -->
# INT03
This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0169
- Accuracy: 1.0
- F1: 1.0
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 0.0 | 50 | 0.6888 | 0.62 | 0.5657 |
| No log | 0.01 | 100 | 0.6817 | 0.66 | 0.5965 |
| No log | 0.01 | 150 | 0.6004 | 0.86 | 0.8553 |
| No log | 0.02 | 200 | 0.4136 | 0.87 | 0.8651 |
| No log | 0.02 | 250 | 0.3550 | 0.89 | 0.8889 |
| No log | 0.03 | 300 | 0.3241 | 0.89 | 0.8889 |
| No log | 0.03 | 350 | 0.3144 | 0.89 | 0.8889 |
| No log | 0.04 | 400 | 0.3146 | 0.89 | 0.8889 |
| No log | 0.04 | 450 | 0.2985 | 0.89 | 0.8889 |
| 0.5219 | 0.05 | 500 | 0.2604 | 0.92 | 0.92 |
| 0.5219 | 0.05 | 550 | 0.2242 | 0.92 | 0.9202 |
| 0.5219 | 0.06 | 600 | 0.1976 | 0.92 | 0.9197 |
| 0.5219 | 0.06 | 650 | 0.1800 | 0.93 | 0.9302 |
| 0.5219 | 0.07 | 700 | 0.1685 | 0.93 | 0.9302 |
| 0.5219 | 0.07 | 750 | 0.1706 | 0.93 | 0.9303 |
| 0.5219 | 0.08 | 800 | 0.1532 | 0.93 | 0.9303 |
| 0.5219 | 0.08 | 850 | 0.1411 | 0.93 | 0.9303 |
| 0.5219 | 0.09 | 900 | 0.1070 | 0.98 | 0.9799 |
| 0.5219 | 0.09 | 950 | 0.0970 | 0.96 | 0.9601 |
| 0.2869 | 0.1 | 1000 | 0.0775 | 0.96 | 0.9601 |
| 0.2869 | 0.1 | 1050 | 0.0789 | 0.97 | 0.9701 |
| 0.2869 | 0.11 | 1100 | 0.0546 | 0.98 | 0.98 |
| 0.2869 | 0.11 | 1150 | 0.0789 | 0.98 | 0.9800 |
| 0.2869 | 0.12 | 1200 | 0.0425 | 0.99 | 0.9900 |
| 0.2869 | 0.12 | 1250 | 0.0443 | 0.99 | 0.9900 |
| 0.2869 | 0.13 | 1300 | 0.0340 | 0.99 | 0.9900 |
| 0.2869 | 0.13 | 1350 | 0.0649 | 0.97 | 0.9700 |
| 0.2869 | 0.14 | 1400 | 0.0241 | 1.0 | 1.0 |
| 0.2869 | 0.14 | 1450 | 0.0215 | 1.0 | 1.0 |
| 0.1754 | 0.15 | 1500 | 0.0146 | 1.0 | 1.0 |
| 0.1754 | 0.15 | 1550 | 0.0125 | 1.0 | 1.0 |
| 0.1754 | 0.16 | 1600 | 0.0122 | 1.0 | 1.0 |
| 0.1754 | 0.16 | 1650 | 0.0110 | 1.0 | 1.0 |
| 0.1754 | 0.17 | 1700 | 0.0092 | 1.0 | 1.0 |
| 0.1754 | 0.17 | 1750 | 0.0117 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|