---
base_model: mehdie/ancient_semitic_bert
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: fine_tuned_ancient_semitic_BERT
  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. -->

# fine_tuned_ancient_semitic_BERT

This model is a fine-tuned version of [mehdie/ancient_semitic_bert](https://huggingface.co/mehdie/ancient_semitic_bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3771
- F1: 0.5652
- F5: 0.5748
- Precision: 0.5417
- Recall: 0.5909

## 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: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F5     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| No log        | 1.0   | 17   | 0.3386          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 34   | 0.3252          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 3.0   | 51   | 0.3188          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 4.0   | 68   | 0.3410          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 5.0   | 85   | 0.3069          | 0.1379 | 0.1080 | 0.5       | 0.08   |
| No log        | 6.0   | 102  | 0.3209          | 0.1379 | 0.1080 | 0.5       | 0.08   |
| No log        | 7.0   | 119  | 0.3432          | 0.2222 | 0.2132 | 0.25      | 0.2    |
| No log        | 8.0   | 136  | 0.3606          | 0.2727 | 0.2592 | 0.3158    | 0.24   |
| No log        | 9.0   | 153  | 0.3319          | 0.2927 | 0.2700 | 0.375     | 0.24   |
| No log        | 10.0  | 170  | 0.3741          | 0.4074 | 0.4193 | 0.3793    | 0.44   |
| No log        | 11.0  | 187  | 0.3008          | 0.3784 | 0.3336 | 0.5833    | 0.28   |
| No log        | 12.0  | 204  | 0.3237          | 0.4231 | 0.4294 | 0.4074    | 0.44   |
| No log        | 13.0  | 221  | 0.2848          | 0.5    | 0.4752 | 0.5789    | 0.44   |
| No log        | 14.0  | 238  | 0.3058          | 0.52   | 0.52   | 0.52      | 0.52   |
| No log        | 15.0  | 255  | 0.2912          | 0.5417 | 0.5332 | 0.5652    | 0.52   |
| No log        | 16.0  | 272  | 0.3005          | 0.4681 | 0.4569 | 0.5       | 0.44   |
| No log        | 17.0  | 289  | 0.3122          | 0.5556 | 0.5717 | 0.5172    | 0.6    |
| No log        | 18.0  | 306  | 0.3670          | 0.5667 | 0.6052 | 0.4857    | 0.68   |
| No log        | 19.0  | 323  | 0.2818          | 0.5926 | 0.6098 | 0.5517    | 0.64   |
| No log        | 20.0  | 340  | 0.3012          | 0.5882 | 0.5927 | 0.5769    | 0.6    |
| No log        | 21.0  | 357  | 0.3288          | 0.6154 | 0.6246 | 0.5926    | 0.64   |
| No log        | 22.0  | 374  | 0.3251          | 0.6250 | 0.6152 | 0.6522    | 0.6    |
| No log        | 23.0  | 391  | 0.3145          | 0.6250 | 0.6152 | 0.6522    | 0.6    |
| No log        | 24.0  | 408  | 0.3128          | 0.68   | 0.68   | 0.68      | 0.68   |
| No log        | 25.0  | 425  | 0.3190          | 0.6538 | 0.6636 | 0.6296    | 0.68   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.17.1
- Tokenizers 0.15.2