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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: summerschool-bert-massive
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. -->
# summerschool-bert-massive
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8479
- Accuracy: 0.8283
- F1: 0.8139
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 3.8604 | 0.1389 | 100 | 3.3964 | 0.2720 | 0.2091 |
| 3.046 | 0.2778 | 200 | 2.5353 | 0.4870 | 0.3971 |
| 2.3977 | 0.4167 | 300 | 2.0141 | 0.6193 | 0.5592 |
| 1.9293 | 0.5556 | 400 | 1.6738 | 0.6803 | 0.6328 |
| 1.6997 | 0.6944 | 500 | 1.4307 | 0.7334 | 0.6937 |
| 1.505 | 0.8333 | 600 | 1.2759 | 0.7772 | 0.7469 |
| 1.3531 | 0.9722 | 700 | 1.1656 | 0.7757 | 0.7445 |
| 1.1651 | 1.1111 | 800 | 1.0720 | 0.7914 | 0.7707 |
| 1.0441 | 1.25 | 900 | 0.9979 | 0.8032 | 0.7838 |
| 1.0021 | 1.3889 | 1000 | 0.9496 | 0.8146 | 0.7977 |
| 0.9732 | 1.5278 | 1100 | 0.8996 | 0.8278 | 0.8116 |
| 0.9025 | 1.6667 | 1200 | 0.8816 | 0.8214 | 0.8053 |
| 0.8952 | 1.8056 | 1300 | 0.8612 | 0.8273 | 0.8128 |
| 0.8435 | 1.9444 | 1400 | 0.8479 | 0.8283 | 0.8139 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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