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tsavage68_-_chat_1000_STEPS_03beta_5e7rate_CDPOSFT-4bits
RichardErkhov/tsavage68_-_chat_1000_STEPS_03beta_5e7rate_CDPOSFT-4bits
tsavage68_-_chat_1000_STEPS_03beta_5e7rate_CDPOSFT-4bits is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
chat_1000_STEPS_03beta_5e7rate_CDPOSFT - bnb 4bits
- Model creator: https://huggingface.co/tsavage68/
- Original model: https://huggingface.co/tsavage68/chat_1000_STEPS_03beta_5e7rate_CDPOSFT/
Original model description:
base_model: tsavage68/chat_600STEPS_1e8rate_SFT tags:
- trl
- dpo
- generated_from_trainer model-index:
- name: chat_1000_STEPS_03beta_5e7rate_CDPOSFT results: []
<!-- 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. -->
chat_1000_STEPS_03beta_5e7rate_CDPOSFT
This model is a fine-tuned version of tsavage68/chat_600STEPS_1e8rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6933
- Rewards/chosen: 0.0002
- Rewards/rejected: -0.0002
- Rewards/accuracies: 0.4242
- Rewards/margins: 0.0004
- Logps/rejected: -18.8025
- Logps/chosen: -16.7538
- Logits/rejected: -0.5979
- Logits/chosen: -0.5978
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-08
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6928 | 0.0977 | 50 | 0.6947 | 0.0015 | 0.0040 | 0.4264 | -0.0024 | -18.7888 | -16.7496 | -0.5974 | -0.5972 |
| 0.6895 | 0.1953 | 100 | 0.6950 | -0.0009 | 0.0022 | 0.3890 | -0.0030 | -18.7948 | -16.7576 | -0.5980 | -0.5979 |
| 0.6932 | 0.2930 | 150 | 0.6934 | 0.0018 | 0.0016 | 0.4308 | 0.0002 | -18.7966 | -16.7487 | -0.5984 | -0.5983 |
| 0.695 | 0.3906 | 200 | 0.6947 | 0.0002 | 0.0027 | 0.3868 | -0.0025 | -18.7930 | -16.7541 | -0.5982 | -0.5981 |
| 0.6971 | 0.4883 | 250 | 0.6938 | 0.0028 | 0.0034 | 0.4220 | -0.0006 | -18.7907 | -16.7453 | -0.5980 | -0.5979 |
| 0.6891 | 0.5859 | 300 | 0.6934 | -0.0003 | -0.0005 | 0.4396 | 0.0002 | -18.8036 | -16.7557 | -0.5988 | -0.5987 |
| 0.6872 | 0.6836 | 350 | 0.6939 | 0.0002 | 0.0010 | 0.4088 | -0.0009 | -18.7985 | -16.7541 | -0.5983 | -0.5982 |
| 0.6953 | 0.7812 | 400 | 0.6964 | -0.0050 | 0.0010 | 0.3846 | -0.0060 | -18.7985 | -16.7713 | -0.5980 | -0.5979 |
| 0.689 | 0.8789 | 450 | 0.6949 | 0.0002 | 0.0031 | 0.4088 | -0.0029 | -18.7915 | -16.7539 | -0.5983 | -0.5982 |
| 0.6935 | 0.9766 | 500 | 0.6920 | 0.0025 | -0.0003 | 0.4154 | 0.0028 | -18.8029 | -16.7461 | -0.5985 | -0.5983 |
| 0.6931 | 1.0742 | 550 | 0.6931 | 0.0014 | 0.0007 | 0.4220 | 0.0007 | -18.7996 | -16.7500 | -0.5979 | -0.5978 |
| 0.6919 | 1.1719 | 600 | 0.6951 | -0.0001 | 0.0032 | 0.3780 | -0.0032 | -18.7914 | -16.7548 | -0.5982 | -0.5980 |
| 0.6916 | 1.2695 | 650 | 0.6930 | 0.0027 | 0.0019 | 0.4110 | 0.0009 | -18.7958 | -16.7455 | -0.5982 | -0.5980 |
| 0.6914 | 1.3672 | 700 | 0.6936 | 0.0017 | 0.0020 | 0.4198 | -0.0003 | -18.7954 | -16.7489 | -0.5975 | -0.5974 |
| 0.6937 | 1.4648 | 750 | 0.6937 | 0.0001 | 0.0006 | 0.4352 | -0.0005 | -18.7999 | -16.7542 | -0.5977 | -0.5976 |
| 0.6953 | 1.5625 | 800 | 0.6948 | -0.0003 | 0.0025 | 0.3934 | -0.0028 | -18.7936 | -16.7556 | -0.5977 | -0.5976 |
| 0.6914 | 1.6602 | 850 | 0.6932 | 0.0004 | -0.0002 | 0.4264 | 0.0006 | -18.8026 | -16.7534 | -0.5979 | -0.5978 |
| 0.6936 | 1.7578 | 900 | 0.6933 | 0.0002 | -0.0002 | 0.4242 | 0.0004 | -18.8025 | -16.7538 | -0.5979 | -0.5978 |
| 0.6925 | 1.8555 | 950 | 0.6933 | 0.0002 | -0.0002 | 0.4242 | 0.0004 | -18.8025 | -16.7538 | -0.5979 | -0.5978 |
| 0.6919 | 1.9531 | 1000 | 0.6933 | 0.0002 | -0.0002 | 0.4242 | 0.0004 | -18.8025 | -16.7538 | -0.5979 | -0.5978 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
- Type
- llama
- Created
- Jan 29, 2025
- Updated
- Jan 29, 2025