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---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: TestForColab
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. -->
# TestForColab
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: 0.6591
- Accuracy: 0.62
- F1: 0.6205
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 0.01 | 50 | 0.6891 | 0.54 | 0.3787 |
| No log | 0.01 | 100 | 0.6893 | 0.54 | 0.3787 |
| No log | 0.02 | 150 | 0.6876 | 0.54 | 0.3787 |
| No log | 0.03 | 200 | 0.6978 | 0.48 | 0.4231 |
| No log | 0.03 | 250 | 0.6899 | 0.5 | 0.4878 |
| No log | 0.04 | 300 | 0.6825 | 0.57 | 0.5577 |
| No log | 0.04 | 350 | 0.6782 | 0.62 | 0.6205 |
| No log | 0.05 | 400 | 0.6692 | 0.6 | 0.5981 |
| No log | 0.06 | 450 | 0.6688 | 0.58 | 0.5664 |
| 0.6773 | 0.06 | 500 | 0.6692 | 0.6 | 0.5966 |
| 0.6773 | 0.07 | 550 | 0.6642 | 0.62 | 0.62 |
| 0.6773 | 0.08 | 600 | 0.6577 | 0.65 | 0.6505 |
| 0.6773 | 0.08 | 650 | 0.6618 | 0.6 | 0.5992 |
| 0.6773 | 0.09 | 700 | 0.6617 | 0.62 | 0.62 |
| 0.6773 | 0.09 | 750 | 0.6641 | 0.62 | 0.6205 |
| 0.6773 | 0.1 | 800 | 0.6573 | 0.62 | 0.62 |
| 0.6773 | 0.11 | 850 | 0.6625 | 0.61 | 0.6096 |
| 0.6773 | 0.11 | 900 | 0.6625 | 0.63 | 0.6303 |
| 0.6773 | 0.12 | 950 | 0.6632 | 0.62 | 0.6181 |
| 0.6414 | 0.13 | 1000 | 0.6613 | 0.62 | 0.6206 |
| 0.6414 | 0.13 | 1050 | 0.6594 | 0.62 | 0.6206 |
| 0.6414 | 0.14 | 1100 | 0.6607 | 0.62 | 0.6206 |
| 0.6414 | 0.14 | 1150 | 0.6580 | 0.62 | 0.6205 |
| 0.6414 | 0.15 | 1200 | 0.6628 | 0.62 | 0.6205 |
| 0.6414 | 0.16 | 1250 | 0.6591 | 0.62 | 0.6205 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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