IE_M2_1000steps_1e5rate_01beta_cSFTDPO
This model is a fine-tuned version of tsavage68/IE_M2_1000steps_1e7rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3743
- Rewards/chosen: -2.2787
- Rewards/rejected: -22.2937
- Rewards/accuracies: 0.4600
- Rewards/margins: 20.0150
- Logps/rejected: -263.9586
- Logps/chosen: -64.9924
- Logits/rejected: -2.7884
- Logits/chosen: -2.7491
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4505 | 0.4 | 50 | 0.3743 | -2.1144 | -14.8883 | 0.4600 | 12.7739 | -189.9051 | -63.3497 | -2.7726 | -2.7468 |
| 0.3812 | 0.8 | 100 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3119 | 1.2 | 150 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3639 | 1.6 | 200 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4332 | 2.0 | 250 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3986 | 2.4 | 300 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3986 | 2.8 | 350 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4505 | 3.2 | 400 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4505 | 3.6 | 450 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4332 | 4.0 | 500 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3292 | 4.4 | 550 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3639 | 4.8 | 600 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4505 | 5.2 | 650 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.4505 | 5.6 | 700 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3639 | 6.0 | 750 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.2426 | 6.4 | 800 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.5025 | 6.8 | 850 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3119 | 7.2 | 900 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3466 | 7.6 | 950 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
| 0.3812 | 8.0 | 1000 | 0.3743 | -2.2787 | -22.2937 | 0.4600 | 20.0150 | -263.9586 | -64.9924 | -2.7884 | -2.7491 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1
- Downloads last month
- 3
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support
Model tree for tsavage68/IE_M2_1000steps_1e5rate_01beta_cSFTDPO
Base model
mistralai/Mistral-7B-Instruct-v0.2
Finetuned
tsavage68/IE_M2_1000steps_1e7rate_SFT