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_01beta_cSFTDPO
results: []
IE_L3_1000steps_1e5rate_01beta_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: -0.6743
- Rewards/rejected: -17.3206
- Rewards/accuracies: 0.7400
- Rewards/margins: 16.6463
- Logps/rejected: -248.8334
- Logps/chosen: -89.5409
- Logits/rejected: -0.7455
- Logits/chosen: -0.5957
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 | -1.4004 | -15.2732 | 0.7400 | 13.8728 | -228.3591 | -96.8015 | -0.9287 | -0.7696 |
| 0.1386 | 0.8 | 100 | 0.1802 | -1.5499 | -16.6031 | 0.7400 | 15.0532 | -241.6585 | -98.2971 | -0.9445 | -0.7764 |
| 0.1386 | 1.2 | 150 | 0.1802 | -0.6661 | -17.0830 | 0.7400 | 16.4169 | -246.4570 | -89.4588 | -0.7451 | -0.5958 |
| 0.1733 | 1.6 | 200 | 0.1802 | -0.6529 | -17.0537 | 0.7400 | 16.4009 | -246.1647 | -89.3264 | -0.7451 | -0.5961 |
| 0.2253 | 2.0 | 250 | 0.1802 | -0.6671 | -17.0542 | 0.7400 | 16.3871 | -246.1687 | -89.4687 | -0.7452 | -0.5962 |
| 0.1386 | 2.4 | 300 | 0.1802 | -0.6548 | -17.0821 | 0.7400 | 16.4273 | -246.4482 | -89.3456 | -0.7451 | -0.5961 |
| 0.1213 | 2.8 | 350 | 0.1802 | -0.6721 | -17.1171 | 0.7400 | 16.4449 | -246.7978 | -89.5189 | -0.7458 | -0.5962 |
| 0.1906 | 3.2 | 400 | 0.1802 | -0.6653 | -17.1157 | 0.7400 | 16.4504 | -246.7844 | -89.4512 | -0.7457 | -0.5962 |
| 0.1906 | 3.6 | 450 | 0.1802 | -0.6617 | -17.1771 | 0.7400 | 16.5154 | -247.3981 | -89.4149 | -0.7446 | -0.5950 |
| 0.2079 | 4.0 | 500 | 0.1802 | -0.6833 | -17.2332 | 0.7400 | 16.5498 | -247.9588 | -89.6311 | -0.7448 | -0.5952 |
| 0.156 | 4.4 | 550 | 0.1802 | -0.6867 | -17.2422 | 0.7400 | 16.5555 | -248.0496 | -89.6649 | -0.7452 | -0.5954 |
| 0.1213 | 4.8 | 600 | 0.1802 | -0.6777 | -17.2605 | 0.7400 | 16.5828 | -248.2325 | -89.5749 | -0.7448 | -0.5947 |
| 0.1906 | 5.2 | 650 | 0.1802 | -0.6873 | -17.3035 | 0.7400 | 16.6161 | -248.6618 | -89.6710 | -0.7453 | -0.5953 |
| 0.2426 | 5.6 | 700 | 0.1802 | -0.6716 | -17.3133 | 0.7400 | 16.6417 | -248.7606 | -89.5142 | -0.7451 | -0.5951 |
| 0.2599 | 6.0 | 750 | 0.1802 | -0.6787 | -17.2980 | 0.7400 | 16.6193 | -248.6074 | -89.5846 | -0.7451 | -0.5953 |
| 0.1213 | 6.4 | 800 | 0.1802 | -0.6753 | -17.3101 | 0.7400 | 16.6349 | -248.7285 | -89.5503 | -0.7448 | -0.5951 |
| 0.2426 | 6.8 | 850 | 0.1802 | -0.6754 | -17.3267 | 0.7400 | 16.6514 | -248.8946 | -89.5515 | -0.7444 | -0.5947 |
| 0.1733 | 7.2 | 900 | 0.1802 | -0.6764 | -17.3102 | 0.7400 | 16.6338 | -248.7291 | -89.5621 | -0.7454 | -0.5955 |
| 0.1386 | 7.6 | 950 | 0.1802 | -0.6732 | -17.3134 | 0.7400 | 16.6401 | -248.7610 | -89.5300 | -0.7454 | -0.5955 |
| 0.156 | 8.0 | 1000 | 0.1802 | -0.6743 | -17.3206 | 0.7400 | 16.6463 | -248.8334 | -89.5409 | -0.7455 | -0.5957 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1