YoungPanda / EU_LLAMA_USA_3

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Model's Last Updated: May 16 2024
text-generation

Introduction of EU_LLAMA_USA_3

Model Details of EU_LLAMA_USA_3

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: winglian/Llama-3-8b-64k-PoSE
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: eu_regulatory_ir
    name: eu2uk
    type: completion
  - path: billsum
    field: text
    type: completion
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
wandb_project: eullama
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 6
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-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: out/checkpoint-424
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 100
evals_per_epoch: 2
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: <|end_of_text|>

out

This model is a fine-tuned version of winglian/Llama-3-8b-64k-PoSE on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7217
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: 6
  • eval_batch_size: 6
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 48
  • total_eval_batch_size: 48
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 2
Training results
Training Loss Epoch Step Validation Loss
1.059 0.0047 1 1.0060
0.9352 0.5 106 0.8914
0.8815 1.0 212 0.8217
0.6349 1.4764 318 0.7732
0.5906 1.9764 424 0.7217
Framework versions
  • Transformers 4.40.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Runs of YoungPanda EU_LLAMA_USA_3 on huggingface.co

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EU_LLAMA_USA_3 huggingface.co is an online trial and call api platform, which integrates EU_LLAMA_USA_3's modeling effects, including api services, and provides a free online trial of EU_LLAMA_USA_3, you can try EU_LLAMA_USA_3 online for free by clicking the link below.

YoungPanda EU_LLAMA_USA_3 online free url in huggingface.co:

https://huggingface.co/YoungPanda/EU_LLAMA_USA_3

EU_LLAMA_USA_3 install

EU_LLAMA_USA_3 is an open source model from GitHub that offers a free installation service, and any user can find EU_LLAMA_USA_3 on GitHub to install. At the same time, huggingface.co provides the effect of EU_LLAMA_USA_3 install, users can directly use EU_LLAMA_USA_3 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

EU_LLAMA_USA_3 install url in huggingface.co:

https://huggingface.co/YoungPanda/EU_LLAMA_USA_3

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