c16205e044
Model: jackf857/llama-3-8b-base-kto-ultrafeedback-4xh200-batch-128-20260427-194056 Source: Original Platform
library_name, base_model, tags, datasets, model-index
| library_name | base_model | tags | datasets | model-index | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | W-61/llama-3-8b-base-sft-ultrachat-8xh200 |
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llama-3-8b-base-kto-ultrafeedback-4xh200-batch-128-20260427-194056
This model is a fine-tuned version of W-61/llama-3-8b-base-sft-ultrachat-8xh200 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.4319
- Rewards/chosen: -0.5716
- Logps/chosen: -345.0196
- Rewards/rejected: -1.4489
- Logps/rejected: -411.8449
- Rewards/margins: 0.8773
- Kl: 0.0
- Logits/chosen: -377414720.0
- Logits/rejected: -376930848.0
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: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.8447 | 0.2094 | 200 | 0.4646 | -0.6301 | -350.8658 | -0.9983 | -366.7805 | 0.3682 | 0.0 | -401673280.0 | -397073248.0 |
| 1.7296 | 0.4188 | 400 | 0.4408 | -0.6904 | -356.8998 | -1.3983 | -406.7836 | 0.7079 | 0.0 | -377831392.0 | -377408832.0 |
| 1.685 | 0.6283 | 600 | 0.4325 | -0.9586 | -383.711 | -1.8718 | -454.1356 | 0.9133 | 0.0 | -388254240.0 | -387494368.0 |
| 1.7464 | 0.8377 | 800 | 0.4319 | -0.5716 | -345.0196 | -1.4489 | -411.8449 | 0.8773 | 0.0 | -377414720.0 | -376930848.0 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4