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Egyptian-Arabic-Translator-Llama-3-8B

Text Generation
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PyTorch
llama
axolotl
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text-generation-inference
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Egyptian-Arabic-Translator-Llama-3-8B / README.md
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metadata
base_model: meta-llama/Meta-Llama-3-8B
library_name: peft
license: llama3
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: llama_3_translator_v3
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

base_model: meta-llama/Meta-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  - path: translation-dataset-v3-train.hf
    type: alpaca
    train_on_split: train

test_datasets:
  - path: translation-dataset-v3-test.hf
    type: alpaca
    split: train

dataset_prepared_path: ./last_run_prepared
output_dir: ./llama_3_translator
hub_model_id: ahmedsamirio/llama_3_translator_v3


sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

adapter: lora
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
  - gate_proj
  - down_proj
  - up_proj
  - q_proj
  - v_proj
  - k_proj
  - o_proj

wandb_project: en_eg_translator
wandb_entity: ahmedsamirio
wandb_name: llama_3_en_eg_translator_v3

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 2
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 10
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: <|end_of_text|>

Visualize in Weights & Biases

Egyptian Arabic Translator Llama-3 8B

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the ahmedsamirio/oasst2-9k-translation dataset.

Model description

This model is an attempt to create a small translation model from English to Egyptian Arabic.

Intended uses & limitations

  • Translating instruction finetuning and text generation datasets

Training and evaluation data

ahmedsamirio/oasst2-9k-translation

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss
0.9661 0.0008 1 1.3816
0.5611 0.1002 123 0.9894
0.6739 0.2004 246 0.8820
0.5168 0.3006 369 0.8229
0.5582 0.4008 492 0.7931
0.552 0.5010 615 0.7814
0.5129 0.6012 738 0.7591
0.5887 0.7014 861 0.7444
0.6359 0.8016 984 0.7293
0.613 0.9018 1107 0.7179
0.5671 1.0020 1230 0.7126
0.4956 1.0847 1353 0.7034
0.5055 1.1849 1476 0.6980
0.4863 1.2851 1599 0.6877
0.4538 1.3853 1722 0.6845
0.4362 1.4855 1845 0.6803
0.4291 1.5857 1968 0.6834
0.6208 1.6859 2091 0.6830
0.582 1.7862 2214 0.6781
0.5001 1.8864 2337 0.6798

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.3
  • Pytorch 2.1.2+cu118
  • Datasets 2.19.1
  • Tokenizers 0.19.1