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---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: MM03-PC
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. -->
# MM03-PC
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: 0.5909
- Accuracy: 0.71
- F1: 0.8304
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 0.0 | 50 | 0.6916 | 0.53 | 0.3672 |
| No log | 0.01 | 100 | 0.6924 | 0.53 | 0.3672 |
| No log | 0.01 | 150 | 0.6922 | 0.53 | 0.3672 |
| No log | 0.01 | 200 | 0.6927 | 0.56 | 0.5593 |
| No log | 0.02 | 250 | 0.6903 | 0.53 | 0.3672 |
| No log | 0.02 | 300 | 0.6884 | 0.53 | 0.3672 |
| No log | 0.03 | 350 | 0.6875 | 0.53 | 0.3842 |
| No log | 0.03 | 400 | 0.6865 | 0.59 | 0.5100 |
| No log | 0.03 | 450 | 0.6835 | 0.59 | 0.5193 |
| 0.6925 | 0.04 | 500 | 0.6792 | 0.58 | 0.5732 |
| 0.6925 | 0.04 | 550 | 0.6717 | 0.74 | 0.7324 |
| 0.6925 | 0.04 | 600 | 0.6558 | 0.73 | 0.7248 |
| 0.6925 | 0.05 | 650 | 0.6456 | 0.65 | 0.6286 |
| 0.6925 | 0.05 | 700 | 0.6371 | 0.74 | 0.7342 |
| 0.6925 | 0.06 | 750 | 0.6353 | 0.64 | 0.6403 |
| 0.6925 | 0.06 | 800 | 0.6331 | 0.72 | 0.7096 |
| 0.6925 | 0.06 | 850 | 0.6298 | 0.73 | 0.7248 |
| 0.6925 | 0.07 | 900 | 0.6341 | 0.69 | 0.6743 |
| 0.6925 | 0.07 | 950 | 0.6302 | 0.61 | 0.6102 |
| 0.6691 | 0.07 | 1000 | 0.6161 | 0.63 | 0.6297 |
| 0.6691 | 0.08 | 1050 | 0.6035 | 0.75 | 0.7486 |
| 0.6691 | 0.08 | 1100 | 0.6015 | 0.74 | 0.7370 |
| 0.6691 | 0.08 | 1150 | 0.5958 | 0.73 | 0.7298 |
| 0.6691 | 0.09 | 1200 | 0.5895 | 0.73 | 0.7263 |
| 0.6691 | 0.09 | 1250 | 0.5921 | 0.73 | 0.7263 |
| 0.6691 | 0.1 | 1300 | 0.5935 | 0.73 | 0.7285 |
| 0.6691 | 0.1 | 1350 | 0.5853 | 0.73 | 0.7275 |
| 0.6691 | 0.1 | 1400 | 0.5952 | 0.74 | 0.7381 |
| 0.6691 | 0.11 | 1450 | 0.5811 | 0.76 | 0.7582 |
| 0.6482 | 0.11 | 1500 | 0.5849 | 0.7 | 0.6933 |
| 0.6482 | 0.11 | 1550 | 0.5827 | 0.71 | 0.7044 |
| 0.6482 | 0.12 | 1600 | 0.5741 | 0.71 | 0.7026 |
| 0.6482 | 0.12 | 1650 | 0.5782 | 0.73 | 0.7275 |
| 0.6482 | 0.12 | 1700 | 0.5704 | 0.74 | 0.7370 |
| 0.6482 | 0.13 | 1750 | 0.5704 | 0.74 | 0.7396 |
| 0.6482 | 0.13 | 1800 | 0.5592 | 0.72 | 0.7154 |
| 0.6482 | 0.14 | 1850 | 0.5661 | 0.72 | 0.7137 |
| 0.6482 | 0.14 | 1900 | 0.5762 | 0.71 | 0.7044 |
| 0.6482 | 0.14 | 1950 | 0.5702 | 0.71 | 0.7044 |
| 0.6226 | 0.15 | 2000 | 0.5677 | 0.73 | 0.7285 |
| 0.6226 | 0.15 | 2050 | 0.5649 | 0.73 | 0.7285 |
| 0.6226 | 0.15 | 2100 | 0.5583 | 0.74 | 0.7370 |
| 0.6226 | 0.16 | 2150 | 0.5712 | 0.7 | 0.6951 |
| 0.6226 | 0.16 | 2200 | 0.5661 | 0.7 | 0.6951 |
| 0.6226 | 0.17 | 2250 | 0.5452 | 0.76 | 0.7573 |
| 0.6226 | 0.17 | 2300 | 0.5448 | 0.75 | 0.7493 |
| 0.6226 | 0.17 | 2350 | 0.5424 | 0.75 | 0.7493 |
| 0.6226 | 0.18 | 2400 | 0.5444 | 0.75 | 0.7477 |
| 0.6226 | 0.18 | 2450 | 0.5400 | 0.75 | 0.7477 |
| 0.6058 | 0.18 | 2500 | 0.5393 | 0.75 | 0.7493 |
| 0.6058 | 0.19 | 2550 | 0.5495 | 0.75 | 0.7486 |
| 0.6058 | 0.19 | 2600 | 0.5309 | 0.76 | 0.7590 |
| 0.6058 | 0.19 | 2650 | 0.5242 | 0.73 | 0.7298 |
| 0.6058 | 0.2 | 2700 | 0.5239 | 0.73 | 0.7298 |
| 0.6058 | 0.2 | 2750 | 0.5201 | 0.71 | 0.7098 |
| 0.6058 | 0.21 | 2800 | 0.5087 | 0.73 | 0.7285 |
| 0.6058 | 0.21 | 2850 | 0.5041 | 0.75 | 0.7486 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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