65 lines
1.7 KiB
Markdown
65 lines
1.7 KiB
Markdown
|
---
|
||
|
|
library_name: transformers
|
||
|
|
license: other
|
||
|
|
base_model: ontocord/1.7b-MixtureVitae-300BT-v1-long_instruct
|
||
|
|
tags:
|
||
|
|
- llama-factory
|
||
|
|
- full
|
||
|
|
- generated_from_trainer
|
||
|
|
model-index:
|
||
|
|
- name: opensci_full_sft_fsdp_offload
|
||
|
|
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. -->
|
||
|
|
|
||
|
|
# opensci_full_sft_fsdp_offload
|
||
|
|
|
||
|
|
This model is a fine-tuned version of [ontocord/1.7b-MixtureVitae-300BT-v1](https://huggingface.co/ontocord/1.7b-MixtureVitae-300BT-v1) on the smoltalk, the longalign and the sealong datasets.
|
||
|
|
The model extends the context length of base model from 4096 to 16384 tokens.
|
||
|
|
|
||
|
|
### NOTE: Because the post-training data is no longer strictly public domain, cc-by and .gov, please do not depend on these constraints on the model output. This is an experimental model.
|
||
|
|
|
||
|
|
## 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: 0.0002
|
||
|
|
- train_batch_size: 4
|
||
|
|
- eval_batch_size: 8
|
||
|
|
- seed: 42
|
||
|
|
- distributed_type: multi-GPU
|
||
|
|
- num_devices: 64
|
||
|
|
- gradient_accumulation_steps: 2
|
||
|
|
- total_train_batch_size: 512
|
||
|
|
- total_eval_batch_size: 512
|
||
|
|
- 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: 0.05
|
||
|
|
- num_epochs: 1.0
|
||
|
|
|
||
|
|
### Training results
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
### Framework versions
|
||
|
|
|
||
|
|
- Transformers 4.55.0
|
||
|
|
- Pytorch 2.6.0+cu124
|
||
|
|
- Datasets 4.0.0
|
||
|
|
- Tokenizers 0.21.4
|