---
base_model: nobody12321/poker-pretrain
tags:
- generated_from_trainer
model-index:
- name: poker-pretraining
  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. -->

# poker-pretraining

This model is a fine-tuned version of [nobody12321/poker-pretrain](https://huggingface.co/nobody12321/poker-pretrain) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7246

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step   | Validation Loss |
|:-------------:|:------:|:------:|:---------------:|
| 2.651         | 0.0183 | 5000   | 2.3357          |
| 2.2946        | 0.0367 | 10000  | 2.2261          |
| 2.2212        | 0.0550 | 15000  | 2.1725          |
| 2.1702        | 0.0733 | 20000  | 2.1131          |
| 2.1332        | 0.0917 | 25000  | 2.0965          |
| 2.1062        | 0.1100 | 30000  | 2.0647          |
| 2.0854        | 0.1283 | 35000  | 2.0518          |
| 2.0688        | 0.1466 | 40000  | 2.0344          |
| 2.0556        | 0.1650 | 45000  | 2.0200          |
| 2.045         | 0.1833 | 50000  | 2.0177          |
| 2.0349        | 0.2016 | 55000  | 1.9994          |
| 2.0254        | 0.2200 | 60000  | 1.9950          |
| 2.0175        | 0.2383 | 65000  | 1.9861          |
| 2.0093        | 0.2566 | 70000  | 1.9792          |
| 2.0013        | 0.2750 | 75000  | 1.9761          |
| 1.9946        | 0.2933 | 80000  | 1.9676          |
| 1.988         | 0.3116 | 85000  | 1.9606          |
| 1.9817        | 0.3299 | 90000  | 1.9544          |
| 1.9729        | 0.3483 | 95000  | 1.9465          |
| 1.9662        | 0.3666 | 100000 | 1.9471          |
| 1.9597        | 0.3849 | 105000 | 1.9351          |
| 1.9532        | 0.4033 | 110000 | 1.9313          |
| 1.9475        | 0.4216 | 115000 | 1.9283          |
| 1.9407        | 0.4399 | 120000 | 1.9223          |
| 1.9356        | 0.4583 | 125000 | 1.9139          |
| 1.9308        | 0.4766 | 130000 | 1.9094          |
| 1.9244        | 0.4949 | 135000 | 1.9038          |
| 1.9194        | 0.5132 | 140000 | 1.8983          |
| 1.9134        | 0.5316 | 145000 | 1.8951          |
| 1.9093        | 0.5499 | 150000 | 1.8904          |
| 1.9038        | 0.5682 | 155000 | 1.8826          |
| 1.898         | 0.5866 | 160000 | 1.8776          |
| 1.8931        | 0.6049 | 165000 | 1.8738          |
| 1.8878        | 0.6232 | 170000 | 1.8685          |
| 1.882         | 0.6416 | 175000 | 1.8633          |
| 1.8755        | 0.6599 | 180000 | 1.8573          |
| 1.87          | 0.6782 | 185000 | 1.8517          |
| 1.8648        | 0.6965 | 190000 | 1.8465          |
| 1.8587        | 0.7149 | 195000 | 1.8407          |
| 1.8537        | 0.7332 | 200000 | 1.8346          |
| 1.8358        | 0.7515 | 205000 | 1.8094          |
| 1.8207        | 0.7699 | 210000 | 1.7976          |
| 1.8109        | 0.7882 | 215000 | 1.7890          |
| 1.8031        | 0.8065 | 220000 | 1.7788          |
| 1.7926        | 0.8249 | 225000 | 1.7671          |
| 1.7821        | 0.8432 | 230000 | 1.7571          |
| 1.7756        | 0.8615 | 235000 | 1.7497          |
| 1.7678        | 0.8799 | 240000 | 1.7423          |
| 1.7627        | 0.8982 | 245000 | 1.7366          |
| 1.7581        | 0.9165 | 250000 | 1.7317          |
| 1.7538        | 0.9348 | 255000 | 1.7286          |
| 1.7513        | 0.9532 | 260000 | 1.7262          |
| 1.75          | 0.9715 | 265000 | 1.7251          |
| 1.7492        | 0.9898 | 270000 | 1.7246          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1