UTI_L3_1000steps_1e5rate_05beta_CSFTDPO
This model is a fine-tuned version of tsavage68/UTI_L3_1000steps_1e5rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0069
- Rewards/chosen: 2.5286
- Rewards/rejected: -48.6639
- Rewards/accuracies: 0.9900
- Rewards/margins: 51.1926
- Logps/rejected: -160.5225
- Logps/chosen: -27.4217
- Logits/rejected: -1.3535
- Logits/chosen: -1.3136
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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0 | 0.6667 | 50 | 0.0071 | 1.6538 | -15.9005 | 0.9900 | 17.5543 | -94.9957 | -29.1714 | -1.3772 | -1.3510 |
| 0.0173 | 1.3333 | 100 | 0.1641 | 5.8391 | -14.1581 | 0.9100 | 19.9972 | -91.5108 | -20.8008 | -1.4149 | -1.3894 |
| 0.0347 | 2.0 | 150 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 |
| 0.0 | 2.6667 | 200 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 |
| 0.0173 | 3.3333 | 250 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 |
| 0.0347 | 4.0 | 300 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 |
| 0.0173 | 4.6667 | 350 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4149 | -1.3535 | -1.3136 |
| 0.0173 | 5.3333 | 400 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 |
| 0.0173 | 6.0 | 450 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 |
| 0.0347 | 6.6667 | 500 | 0.0069 | 2.5321 | -48.6719 | 0.9900 | 51.2040 | -160.5385 | -27.4148 | -1.3535 | -1.3136 |
| 0.0 | 7.3333 | 550 | 0.0069 | 2.5319 | -48.6721 | 0.9900 | 51.2040 | -160.5388 | -27.4152 | -1.3535 | -1.3136 |
| 0.0347 | 8.0 | 600 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0 | 8.6667 | 650 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0173 | 9.3333 | 700 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0 | 10.0 | 750 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0173 | 10.6667 | 800 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0 | 11.3333 | 850 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0 | 12.0 | 900 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0173 | 12.6667 | 950 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
| 0.0 | 13.3333 | 1000 | 0.0069 | 2.5286 | -48.6639 | 0.9900 | 51.1926 | -160.5225 | -27.4217 | -1.3535 | -1.3136 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for tsavage68/UTI_L3_1000steps_1e5rate_05beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/UTI_L3_1000steps_1e5rate_SFT