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library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: rationale_model_e10
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. -->
# rationale_model_e10
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9041
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.0662 | 0.0477 | 500 | 1.9416 |
| 1.8844 | 0.0954 | 1000 | 1.9136 |
| 1.7819 | 0.1431 | 1500 | 1.9041 |
| 1.6587 | 0.1908 | 2000 | 1.9142 |
| 1.5711 | 0.2385 | 2500 | 1.9290 |
| 1.4686 | 0.2862 | 3000 | 1.9362 |
| 1.3787 | 0.3338 | 3500 | 2.0431 |
| 1.2464 | 0.3815 | 4000 | 2.0219 |
| 1.1407 | 0.4292 | 4500 | 2.0494 |
| 1.0591 | 0.4769 | 5000 | 2.0871 |
| 0.9351 | 0.5246 | 5500 | 2.1374 |
| 0.8295 | 0.5723 | 6000 | 2.1954 |
| 0.7724 | 0.6200 | 6500 | 2.2344 |
| 0.6506 | 0.6677 | 7000 | 2.2971 |
| 0.6109 | 0.7154 | 7500 | 2.3390 |
| 0.5302 | 0.7631 | 8000 | 2.4308 |
| 0.4378 | 0.8108 | 8500 | 2.5308 |
| 0.383 | 0.8585 | 9000 | 2.6438 |
| 0.3419 | 0.9061 | 9500 | 2.6942 |
| 0.2983 | 0.9538 | 10000 | 2.7862 |
| 0.2568 | 1.0015 | 10500 | 2.9069 |
| 0.186 | 1.0492 | 11000 | 2.8744 |
| 0.1799 | 1.0969 | 11500 | 2.9436 |
| 0.1831 | 1.1446 | 12000 | 2.9253 |
| 0.1751 | 1.1923 | 12500 | 3.0272 |
| 0.1652 | 1.2400 | 13000 | 3.0354 |
| 0.1644 | 1.2877 | 13500 | 3.0101 |
| 0.1569 | 1.3354 | 14000 | 3.0530 |
| 0.1554 | 1.3831 | 14500 | 3.0933 |
| 0.1498 | 1.4308 | 15000 | 3.1092 |
| 0.1424 | 1.4784 | 15500 | 3.1997 |
| 0.1417 | 1.5261 | 16000 | 3.1469 |
| 0.1385 | 1.5738 | 16500 | 3.2502 |
| 0.1355 | 1.6215 | 17000 | 3.2343 |
| 0.1323 | 1.6692 | 17500 | 3.2179 |
| 0.1279 | 1.7169 | 18000 | 3.2491 |
| 0.1268 | 1.7646 | 18500 | 3.2739 |
| 0.1206 | 1.8123 | 19000 | 3.3483 |
| 0.1211 | 1.8600 | 19500 | 3.3606 |
| 0.118 | 1.9077 | 20000 | 3.3723 |
| 0.1162 | 1.9554 | 20500 | 3.3527 |
| 0.1124 | 2.0031 | 21000 | 3.5134 |
| 0.0983 | 2.0507 | 21500 | 3.4884 |
| 0.1002 | 2.0984 | 22000 | 3.5197 |
| 0.1018 | 2.1461 | 22500 | 3.5413 |
| 0.0981 | 2.1938 | 23000 | 3.5697 |
| 0.097 | 2.2415 | 23500 | 3.5927 |
| 0.0949 | 2.2892 | 24000 | 3.5983 |
| 0.0971 | 2.3369 | 24500 | 3.6530 |
| 0.0952 | 2.3846 | 25000 | 3.6665 |
| 0.0973 | 2.4323 | 25500 | 3.6585 |
| 0.0915 | 2.4800 | 26000 | 3.7384 |
| 0.0918 | 2.5277 | 26500 | 3.7284 |
| 0.0918 | 2.5754 | 27000 | 3.7835 |
| 0.0885 | 2.6230 | 27500 | 3.8170 |
| 0.0891 | 2.6707 | 28000 | 3.8412 |
| 0.0901 | 2.7184 | 28500 | 3.8526 |
| 0.0878 | 2.7661 | 29000 | 3.8645 |
| 0.0864 | 2.8138 | 29500 | 3.9049 |
| 0.0866 | 2.8615 | 30000 | 3.9255 |
| 0.0853 | 2.9092 | 30500 | 3.9378 |
| 0.0858 | 2.9569 | 31000 | 3.9455 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.3.0
- Datasets 2.14.4
- Tokenizers 0.20.3
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