metadata
library_name: transformers
license: llama3
base_model: tsavage68/IE_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: IE_L3_1000steps_1e5rate_05beta_cSFTDPO
results: []
IE_L3_1000steps_1e5rate_05beta_cSFTDPO
This model is a fine-tuned version of tsavage68/IE_L3_1000steps_1e6rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1802
- Rewards/chosen: -1.9138
- Rewards/rejected: -16.8689
- Rewards/accuracies: 0.7400
- Rewards/margins: 14.9551
- Logps/rejected: -109.3650
- Logps/chosen: -86.6253
- Logits/rejected: -0.7926
- Logits/chosen: -0.7113
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1906 | 0.4 | 50 | 0.1802 | -1.6520 | -15.8076 | 0.7400 | 14.1556 | -107.2424 | -86.1018 | -0.7917 | -0.7117 |
| 0.1386 | 0.8 | 100 | 0.1802 | -1.8267 | -16.5557 | 0.7400 | 14.7290 | -108.7386 | -86.4511 | -0.7906 | -0.7103 |
| 0.1386 | 1.2 | 150 | 0.1802 | -1.8547 | -16.5627 | 0.7400 | 14.7080 | -108.7527 | -86.5072 | -0.7921 | -0.7119 |
| 0.1733 | 1.6 | 200 | 0.1802 | -1.8689 | -16.5821 | 0.7400 | 14.7132 | -108.7914 | -86.5355 | -0.7914 | -0.7112 |
| 0.2253 | 2.0 | 250 | 0.1802 | -1.8605 | -16.6156 | 0.7400 | 14.7552 | -108.8585 | -86.5187 | -0.7914 | -0.7110 |
| 0.1386 | 2.4 | 300 | 0.1802 | -1.8594 | -16.6192 | 0.7400 | 14.7598 | -108.8657 | -86.5166 | -0.7911 | -0.7110 |
| 0.1213 | 2.8 | 350 | 0.1802 | -1.8731 | -16.6287 | 0.7400 | 14.7556 | -108.8846 | -86.5440 | -0.7901 | -0.7097 |
| 0.1906 | 3.2 | 400 | 0.1802 | -1.8656 | -16.7018 | 0.7400 | 14.8363 | -109.0309 | -86.5289 | -0.7915 | -0.7108 |
| 0.1906 | 3.6 | 450 | 0.1802 | -1.8643 | -16.6935 | 0.7400 | 14.8292 | -109.0142 | -86.5264 | -0.7910 | -0.7101 |
| 0.2079 | 4.0 | 500 | 0.1802 | -1.8487 | -16.6943 | 0.7400 | 14.8456 | -109.0159 | -86.4952 | -0.7915 | -0.7105 |
| 0.156 | 4.4 | 550 | 0.1802 | -1.8609 | -16.7207 | 0.7400 | 14.8598 | -109.0686 | -86.5195 | -0.7923 | -0.7110 |
| 0.1213 | 4.8 | 600 | 0.1802 | -1.8764 | -16.7597 | 0.7400 | 14.8833 | -109.1467 | -86.5507 | -0.7921 | -0.7111 |
| 0.1906 | 5.2 | 650 | 0.1802 | -1.8747 | -16.8014 | 0.7400 | 14.9267 | -109.2300 | -86.5471 | -0.7919 | -0.7103 |
| 0.2426 | 5.6 | 700 | 0.1802 | -1.8684 | -16.7797 | 0.7400 | 14.9113 | -109.1867 | -86.5346 | -0.7925 | -0.7117 |
| 0.2599 | 6.0 | 750 | 0.1802 | -1.8981 | -16.8462 | 0.7400 | 14.9481 | -109.3197 | -86.5939 | -0.7929 | -0.7119 |
| 0.1213 | 6.4 | 800 | 0.1802 | -1.8918 | -16.8690 | 0.7400 | 14.9772 | -109.3652 | -86.5813 | -0.7929 | -0.7119 |
| 0.2426 | 6.8 | 850 | 0.1802 | -1.8689 | -16.8074 | 0.7400 | 14.9386 | -109.2421 | -86.5355 | -0.7932 | -0.7122 |
| 0.1733 | 7.2 | 900 | 0.1802 | -1.8717 | -16.8482 | 0.7400 | 14.9765 | -109.3236 | -86.5412 | -0.7924 | -0.7110 |
| 0.1386 | 7.6 | 950 | 0.1802 | -1.9143 | -16.8686 | 0.7400 | 14.9543 | -109.3644 | -86.6264 | -0.7926 | -0.7113 |
| 0.156 | 8.0 | 1000 | 0.1802 | -1.9138 | -16.8689 | 0.7400 | 14.9551 | -109.3650 | -86.6253 | -0.7926 | -0.7113 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1