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Tukan-1.1B-Chat-v0.6_dpo
alexredna/Tukan-1.1B-Chat-v0.6_dpo
Tukan-1.1B-Chat-v0.6_dpo is a machine learning model from alexredna. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Jan 15, 2024
- Updated
- Jan 16, 2024
- SHA
- c686a6ba
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
Tukan-1.1B-Chat-v0.6_dpo
This model is a fine-tuned version of alexredna/Tukan-1.1B-Chat-v0.6 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6664
- Rewards/chosen: -0.0698
- Rewards/rejected: -0.1297
- Rewards/accuracies: 0.6667
- Rewards/margins: 0.0600
- Logps/rejected: -364.0182
- Logps/chosen: -408.6165
- Logits/rejected: -2.1219
- Logits/chosen: -2.2568
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: 3e-07
- train_batch_size: 5
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6819 | 0.99 | 61 | 0.6804 | -0.0465 | -0.0746 | 0.6318 | 0.0281 | -363.4672 | -408.3842 | -2.1356 | -2.2671 |
| 0.6718 | 2.0 | 123 | 0.6719 | -0.0689 | -0.1170 | 0.6269 | 0.0482 | -363.8911 | -408.6075 | -2.1242 | -2.2588 |
| 0.6687 | 2.97 | 183 | 0.6664 | -0.0698 | -0.1297 | 0.6667 | 0.0600 | -364.0182 | -408.6165 | -2.1219 | -2.2568 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
Framework versions
- PEFT 0.6.1
- Library
- peft
- Created
- Jan 15, 2024
- Updated
- Jan 16, 2024