Downloads · 30 days
3
14% of all-time downloads
model_3k_maxtokens_800_step1_trajectories_trained_only
tttx/model_3k_maxtokens_800_step1_trajectories_trained_only
model_3k_maxtokens_800_step1_trajectories_trained_only is a machine learning model from tttx. 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. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
22
Public
Repo size
2.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.1 GB · 99%
At a glance
- Library
- peft
- License
- mit
- Model type
- qwen2
- Access
- Public
- Created
- Feb 24, 2025
- Updated
- Feb 24, 2025
- SHA
- 7042e1ee
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. -->
model_3k_maxtokens_800_step1_trajectories_trained_only
This model is a fine-tuned version of tttx/sft-32b-020925-19k-5ep on the tttx/3k_forcing_022225_800_buffer dataset.
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: 8e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 100
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use 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: 3
Training results
Framework versions
- PEFT 0.13.2
- Transformers 4.47.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- peft
- Type
- qwen2
- License
- mit
- Created
- Feb 24, 2025
- Updated
- Feb 24, 2025