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# S04

This model is a fine-tuned version of [Anwaarma/Merged-Server-praj](https://huggingface.co/Anwaarma/Merged-Server-praj) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5249
- Accuracy: 0.71
- F1: 0.8304

## 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: 4e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.01  | 50   | 0.6296          | 0.65     | 0.6505 |
| No log        | 0.01  | 100  | 0.6280          | 0.67     | 0.6697 |
| No log        | 0.02  | 150  | 0.6210          | 0.67     | 0.6665 |
| No log        | 0.03  | 200  | 0.6583          | 0.65     | 0.6505 |
| No log        | 0.03  | 250  | 0.6650          | 0.65     | 0.6505 |
| No log        | 0.04  | 300  | 0.6613          | 0.67     | 0.6697 |
| No log        | 0.04  | 350  | 0.6663          | 0.65     | 0.6502 |
| No log        | 0.05  | 400  | 0.6704          | 0.67     | 0.6702 |
| No log        | 0.06  | 450  | 0.6570          | 0.68     | 0.6794 |
| 0.6123        | 0.06  | 500  | 0.6430          | 0.65     | 0.6502 |
| 0.6123        | 0.07  | 550  | 0.6558          | 0.64     | 0.6404 |
| 0.6123        | 0.08  | 600  | 0.6662          | 0.64     | 0.64   |
| 0.6123        | 0.08  | 650  | 0.6547          | 0.64     | 0.6406 |
| 0.6123        | 0.09  | 700  | 0.6407          | 0.66     | 0.6605 |
| 0.6123        | 0.09  | 750  | 0.6238          | 0.66     | 0.6605 |
| 0.6123        | 0.1   | 800  | 0.6223          | 0.68     | 0.6794 |
| 0.6123        | 0.11  | 850  | 0.6006          | 0.66     | 0.6604 |
| 0.6123        | 0.11  | 900  | 0.6294          | 0.68     | 0.6773 |
| 0.6123        | 0.12  | 950  | 0.6195          | 0.66     | 0.66   |
| 0.6014        | 0.13  | 1000 | 0.6119          | 0.65     | 0.6505 |
| 0.6014        | 0.13  | 1050 | 0.6230          | 0.67     | 0.6702 |
| 0.6014        | 0.14  | 1100 | 0.6410          | 0.69     | 0.6905 |
| 0.6014        | 0.14  | 1150 | 0.6306          | 0.67     | 0.6705 |
| 0.6014        | 0.15  | 1200 | 0.6476          | 0.7      | 0.6994 |
| 0.6014        | 0.16  | 1250 | 0.6244          | 0.67     | 0.6705 |
| 0.6014        | 0.16  | 1300 | 0.6078          | 0.69     | 0.6897 |
| 0.6014        | 0.17  | 1350 | 0.5869          | 0.67     | 0.6705 |
| 0.6014        | 0.18  | 1400 | 0.6164          | 0.67     | 0.6665 |
| 0.6014        | 0.18  | 1450 | 0.6054          | 0.65     | 0.6505 |
| 0.5906        | 0.19  | 1500 | 0.5947          | 0.67     | 0.6705 |
| 0.5906        | 0.19  | 1550 | 0.5765          | 0.69     | 0.6905 |
| 0.5906        | 0.2   | 1600 | 0.5677          | 0.69     | 0.6905 |
| 0.5906        | 0.21  | 1650 | 0.5828          | 0.7      | 0.7005 |
| 0.5906        | 0.21  | 1700 | 0.6249          | 0.67     | 0.6689 |
| 0.5906        | 0.22  | 1750 | 0.5833          | 0.69     | 0.6905 |
| 0.5906        | 0.23  | 1800 | 0.5838          | 0.68     | 0.6804 |
| 0.5906        | 0.23  | 1850 | 0.5923          | 0.7      | 0.7004 |
| 0.5906        | 0.24  | 1900 | 0.5749          | 0.69     | 0.6905 |
| 0.5906        | 0.25  | 1950 | 0.5769          | 0.7      | 0.7004 |
| 0.5736        | 0.25  | 2000 | 0.5706          | 0.7      | 0.7005 |
| 0.5736        | 0.26  | 2050 | 0.5967          | 0.69     | 0.6897 |
| 0.5736        | 0.26  | 2100 | 0.5866          | 0.69     | 0.6897 |
| 0.5736        | 0.27  | 2150 | 0.5901          | 0.7      | 0.7    |
| 0.5736        | 0.28  | 2200 | 0.5771          | 0.7      | 0.7004 |
| 0.5736        | 0.28  | 2250 | 0.5616          | 0.69     | 0.6905 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "Anwaarma/Merged-Server-praj", "model-index": [{"name": "S04", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:Anwaarma/Merged-Server-praj autotrain_compatible endpoints_compatible region:us