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---
base_model: google/gemma-2-2b
library_name: peft
license: gemma
tags:
- generated_from_trainer
model-index:
- name: gemma-2-2b-chess
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. -->
# gemma-2-2b-chess
This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b).
It achieves the following results on the evaluation set:
- Loss: 1.0489
[gemma-2-2b-chess-adapter](https://huggingface.co/diabolic6045/gemma-2-2b-chess-adapter)
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0562 | 0.3959 | 500 | 1.0697 |
| 1.0272 | 0.7918 | 1000 | 1.0489 |
<div style="display: flex; justify-content: space-around;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64020d3e82bbdfe4b7c46cc9/6jiB_BWuLXZ1AXi1Icn6k.png" alt="UI Image 1" style="width: 85%;height: 75%;"/></div>
<div style="display: flex; justify-content: space-around;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64020d3e82bbdfe4b7c46cc9/uAUcRCSvvIydrC6KkW5Hq.png" alt="UI Image 2" style="width: 85%;height: 75%;"/></div>
<div style="display: flex; justify-content: space-around;">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64020d3e82bbdfe4b7c46cc9/Yp-E3C062ekk78PlR9SjA.png" alt="UI Image 2" style="width: 85%;height: 75%;"/></div>
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
|