File size: 3,788 Bytes
5f5c172 |
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: MM05
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. -->
# MM05
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: 0.3184
- Accuracy: 0.99
- F1: 0.9950
## 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: 3e-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: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 0.0 | 50 | 0.6884 | 0.58 | 0.4258 |
| No log | 0.01 | 100 | 0.6988 | 0.42 | 0.2485 |
| No log | 0.01 | 150 | 0.6952 | 0.42 | 0.2485 |
| No log | 0.02 | 200 | 0.6886 | 0.58 | 0.4258 |
| No log | 0.02 | 250 | 0.6889 | 0.59 | 0.4481 |
| No log | 0.02 | 300 | 0.6920 | 0.59 | 0.5916 |
| No log | 0.03 | 350 | 0.6917 | 0.57 | 0.5535 |
| No log | 0.03 | 400 | 0.6947 | 0.45 | 0.3250 |
| No log | 0.04 | 450 | 0.6541 | 0.69 | 0.6866 |
| 0.6877 | 0.04 | 500 | 0.6117 | 0.7 | 0.6829 |
| 0.6877 | 0.04 | 550 | 0.5938 | 0.71 | 0.7030 |
| 0.6877 | 0.05 | 600 | 0.5851 | 0.74 | 0.7390 |
| 0.6877 | 0.05 | 650 | 0.5721 | 0.77 | 0.7645 |
| 0.6877 | 0.06 | 700 | 0.5612 | 0.77 | 0.7704 |
| 0.6877 | 0.06 | 750 | 0.5368 | 0.76 | 0.7612 |
| 0.6877 | 0.06 | 800 | 0.5013 | 0.77 | 0.7696 |
| 0.6877 | 0.07 | 850 | 0.4831 | 0.78 | 0.7792 |
| 0.6877 | 0.07 | 900 | 0.4831 | 0.78 | 0.7792 |
| 0.6877 | 0.08 | 950 | 0.4573 | 0.8 | 0.7886 |
| 0.5813 | 0.08 | 1000 | 0.4576 | 0.79 | 0.7792 |
| 0.5813 | 0.08 | 1050 | 0.4483 | 0.81 | 0.7956 |
| 0.5813 | 0.09 | 1100 | 0.4377 | 0.8 | 0.7886 |
| 0.5813 | 0.09 | 1150 | 0.4297 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1200 | 0.4287 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1250 | 0.4301 | 0.81 | 0.7956 |
| 0.5813 | 0.1 | 1300 | 0.4286 | 0.81 | 0.7956 |
| 0.5813 | 0.11 | 1350 | 0.4193 | 0.81 | 0.7956 |
| 0.5813 | 0.11 | 1400 | 0.4088 | 0.81 | 0.7956 |
| 0.5813 | 0.12 | 1450 | 0.4107 | 0.81 | 0.7956 |
| 0.4699 | 0.12 | 1500 | 0.4016 | 0.81 | 0.7956 |
| 0.4699 | 0.12 | 1550 | 0.4056 | 0.81 | 0.7956 |
| 0.4699 | 0.13 | 1600 | 0.4095 | 0.81 | 0.7956 |
| 0.4699 | 0.13 | 1650 | 0.3973 | 0.81 | 0.7956 |
| 0.4699 | 0.14 | 1700 | 0.3907 | 0.81 | 0.7956 |
| 0.4699 | 0.14 | 1750 | 0.3907 | 0.81 | 0.7956 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|