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---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BP-test1
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. -->
# BP-test1
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: 0.1958
- Accuracy: 0.95
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.01 | 50 | 0.6942 | 0.45 |
| No log | 0.02 | 100 | 0.6915 | 0.57 |
| No log | 0.03 | 150 | 0.6879 | 0.55 |
| No log | 0.04 | 200 | 0.6904 | 0.56 |
| No log | 0.05 | 250 | 0.6847 | 0.56 |
| No log | 0.06 | 300 | 0.6693 | 0.56 |
| No log | 0.07 | 350 | 0.5499 | 0.9 |
| No log | 0.08 | 400 | 0.4220 | 0.93 |
| No log | 0.09 | 450 | 0.3421 | 0.93 |
| 0.6127 | 0.1 | 500 | 0.2987 | 0.93 |
| 0.6127 | 0.11 | 550 | 0.2704 | 0.93 |
| 0.6127 | 0.12 | 600 | 0.2530 | 0.93 |
| 0.6127 | 0.13 | 650 | 0.2199 | 0.93 |
| 0.6127 | 0.14 | 700 | 0.2204 | 0.93 |
| 0.6127 | 0.15 | 750 | 0.1965 | 0.95 |
| 0.6127 | 0.16 | 800 | 0.1944 | 0.95 |
| 0.6127 | 0.17 | 850 | 0.1942 | 0.95 |
| 0.6127 | 0.18 | 900 | 0.1938 | 0.95 |
| 0.6127 | 0.19 | 950 | 0.1950 | 0.95 |
| 0.2388 | 0.2 | 1000 | 0.1943 | 0.95 |
| 0.2388 | 0.2 | 1050 | 0.1939 | 0.95 |
| 0.2388 | 0.21 | 1100 | 0.1939 | 0.95 |
| 0.2388 | 0.22 | 1150 | 0.1928 | 0.95 |
| 0.2388 | 0.23 | 1200 | 0.1937 | 0.95 |
| 0.2388 | 0.24 | 1250 | 0.1958 | 0.95 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|