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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca
model-index:
- name: POEMS-CAMELBERT-CA-RUN4-20-fullData
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. -->
# POEMS-CAMELBERT-CA-RUN4-20-fullData
This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-ca](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1172
- Accuracy: 0.6210
- F1: 0.6210
- Precision: 0.6210
- Recall: 0.6210
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1804 | 1.0 | 568 | 1.1103 | 0.5066 | 0.5066 | 0.5066 | 0.5066 |
| 0.9771 | 2.0 | 1136 | 0.9937 | 0.5847 | 0.5847 | 0.5847 | 0.5847 |
| 0.8057 | 3.0 | 1704 | 1.0751 | 0.5882 | 0.5882 | 0.5882 | 0.5882 |
| 0.6404 | 4.0 | 2272 | 1.1029 | 0.6011 | 0.6011 | 0.6011 | 0.6011 |
| 0.4956 | 5.0 | 2840 | 1.1222 | 0.6064 | 0.6064 | 0.6064 | 0.6064 |
| 0.3742 | 6.0 | 3408 | 1.2714 | 0.6077 | 0.6077 | 0.6077 | 0.6077 |
| 0.2881 | 7.0 | 3976 | 1.5337 | 0.5931 | 0.5931 | 0.5931 | 0.5931 |
| 0.2153 | 8.0 | 4544 | 1.6150 | 0.5984 | 0.5984 | 0.5984 | 0.5984 |
| 0.1663 | 9.0 | 5112 | 1.7246 | 0.6037 | 0.6037 | 0.6037 | 0.6037 |
| 0.1266 | 10.0 | 5680 | 2.0767 | 0.5984 | 0.5984 | 0.5984 | 0.5984 |
| 0.1064 | 11.0 | 6248 | 2.1690 | 0.6161 | 0.6161 | 0.6161 | 0.6161 |
| 0.0895 | 12.0 | 6816 | 2.4732 | 0.6068 | 0.6068 | 0.6068 | 0.6068 |
| 0.0794 | 13.0 | 7384 | 2.4153 | 0.6095 | 0.6095 | 0.6095 | 0.6095 |
| 0.0555 | 14.0 | 7952 | 2.8754 | 0.6037 | 0.6037 | 0.6037 | 0.6037 |
| 0.0502 | 15.0 | 8520 | 2.8673 | 0.6121 | 0.6121 | 0.6121 | 0.6121 |
| 0.0383 | 16.0 | 9088 | 2.9805 | 0.6139 | 0.6139 | 0.6139 | 0.6139 |
| 0.0329 | 17.0 | 9656 | 3.0402 | 0.6188 | 0.6188 | 0.6188 | 0.6188 |
| 0.0237 | 18.0 | 10224 | 3.0225 | 0.6263 | 0.6263 | 0.6263 | 0.6263 |
| 0.0173 | 19.0 | 10792 | 3.0629 | 0.6206 | 0.6206 | 0.6206 | 0.6206 |
| 0.0169 | 20.0 | 11360 | 3.1172 | 0.6210 | 0.6210 | 0.6210 | 0.6210 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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