Downloads · 30 days
18
47% of all-time downloads
martimfasantos_-_tinyllama-1.1b-mt-sft-full-awq
RichardErkhov/martimfasantos_-_tinyllama-1.1b-mt-sft-full-awq
martimfasantos_-_tinyllama-1.1b-mt-sft-full-awq 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.
All-time downloads
38
Public
Parameters
1.1B
766 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors766 MB · 99%
Parameter types
How the weights are stored.
I32969M · 88%
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
tinyllama-1.1b-mt-sft-full - AWQ
- Model creator: https://huggingface.co/martimfasantos/
- Original model: https://huggingface.co/martimfasantos/tinyllama-1.1b-mt-sft-full/
Original model description:
license: apache-2.0 base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer datasets:
- haoranxu/ALMA-Human-Parallel model-index:
- name: tinyllama-1.1b-mt-sft-full 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. -->
tinyllama-1.1b-mt-sft-full
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T on the haoranxu/ALMA-Human-Parallel dataset. It achieves the following results on the evaluation set:
- Loss: 1.6920
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- 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_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5838 | 1.0 | 739 | 1.6892 |
| 1.5051 | 2.0 | 1478 | 1.6920 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
- Type
- llama
- Created
- Dec 25, 2024
- Updated
- Dec 25, 2024