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llama3.1-8B-Instruct-rus-test-v3
anastas5/llama3.1-8B-Instruct-rus-test-v3
llama3.1-8B-Instruct-rus-test-v3 is a machine learning model from anastas5. 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 transformers. The card lists the license as llama3.1.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- llama3.1
- Access
- Public
- Created
- Oct 24, 2024
- Updated
- Oct 24, 2024
- SHA
- 3fac8bcc
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. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.1
base_model: anastas5/llama3.1-8B-Instruct-rus-test-v2
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: anastas5/dataset-rus-test-six
type: sharegpt
conversation: llama-3
dataset_prepared_path: /home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/prepared_tagengo_rus
val_set_size: 0.05
output_dir: /home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/output_llama3_8b_gpt_4o_ru
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
use_wandb: false
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 5
eval_table_size:
saves_per_epoch: 1
debug:
weight_decay: 0.0
special_tokens:
pad_token: <|end_of_text|>
home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/output_llama3_8b_gpt_4o_ru
This model is a fine-tuned version of anastas5/llama3.1-8B-Instruct-rus-test-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7729
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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.957 | 0.0769 | 1 | 0.8838 |
| 0.9398 | 0.2308 | 3 | 0.8762 |
| 1.0969 | 0.4615 | 6 | 0.8373 |
| 0.9608 | 0.6923 | 9 | 0.8226 |
| 0.8364 | 0.9231 | 12 | 0.8146 |
| 0.7566 | 1.1154 | 15 | 0.7914 |
| 0.7927 | 1.3462 | 18 | 0.7818 |
| 0.74 | 1.5769 | 21 | 0.7784 |
| 0.7247 | 1.8077 | 24 | 0.7783 |
| 0.7261 | 2.0385 | 27 | 0.7748 |
| 0.7255 | 2.2308 | 30 | 0.7727 |
| 0.6439 | 2.4615 | 33 | 0.7726 |
| 0.5354 | 2.6923 | 36 | 0.7725 |
| 0.638 | 2.9231 | 39 | 0.7734 |
| 0.6246 | 3.0769 | 42 | 0.7726 |
| 0.5374 | 3.3077 | 45 | 0.7726 |
| 0.5539 | 3.5385 | 48 | 0.7729 |
| 0.6056 | 3.7692 | 51 | 0.7729 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- transformers
- License
- llama3.1
- Created
- Oct 24, 2024
- Updated
- Oct 24, 2024