ahmedsamirio
/

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

@@ -1,233 +1,242 @@
----
-base_model: meta-llama/Meta-Llama-3-8B
-license: llama3
-tags:
-- axolotl
-- generated_from_trainer
-model-index:
-- name: Egyptian-Arabic-Translator-Llama-3-8B
-  results: []
----
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-<details><summary>See axolotl config</summary>
-axolotl version: `0.4.1`
-```yaml
-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|>
-```
-</details><br>
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ahmedsamirio/en_eg_translator/runs/hwzxxt0r)
-# Egyptian Arabic Translator Llama-3 8B
-This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the [ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/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
-## Inference code
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
-tokenizer = AutoTokenizer.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B")
-model = AutoModelForCausalLM.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B")
-pipe = pipeline(task='text-generation', model=model, tokenizer=tokenizer)
-en_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-### Instruction:
-Translate the following text to English.
-### Input:
-{text}
-### Response:
-"""
-ar_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-### Instruction:
-Translate the following text to Arabic.
-### Input:
-{text}
-### Response:
-"""
-eg_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-### Instruction:
-Translate the following text to Egyptian Arabic.
-### Input:
-{text}
-### Response:
-"""
-text = """Some habits are known as "keystone habits," and these influence the formation of other habits. \
-For example, identifying as the type of person who takes care of their body and is in the habit of exercising regularly, \
-can also influence eating better and using credit cards less. In business, \
-safety can be a keystone habit that influences other habits that result in greater productivity.[17]"""
-ar_text = pipe(ar_template.format(text=text),
-               max_new_tokens=256,
-               do_sample=True,
-               temperature=0.3,
-               top_p=0.5)
-eg_text = pipe(eg_template.format(text=ar_text),
-               max_new_tokens=256,
-               do_sample=True,
-               temperature=0.3,
-               top_p=0.5)
-print("Original Text:" text)
-print("\nArabic Translation:", ar_text)
-print("\nEgyptian Arabic Translation:", eg_text)
-```
-## Training and evaluation data
-[ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/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

+---
+base_model: meta-llama/Meta-Llama-3-8B
+license: llama3
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: Egyptian-Arabic-Translator-Llama-3-8B
+  results: []
+datasets:
+- proj-persona/PersonaHub
+language:
+- ar
+- en
+metrics:
+- accuracy
+library_name: adapter-transformers
+pipeline_tag: text-classification
+---
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+axolotl version: `0.4.1`
+```yaml
+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|>
+```
+</details><br>
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ahmedsamirio/en_eg_translator/runs/hwzxxt0r)
+# Egyptian Arabic Translator Llama-3 8B
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the [ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/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
+## Inference code
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+tokenizer = AutoTokenizer.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B")
+model = AutoModelForCausalLM.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B")
+pipe = pipeline(task='text-generation', model=model, tokenizer=tokenizer)
+en_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+### Instruction:
+Translate the following text to English.
+### Input:
+{text}
+### Response:
+"""
+ar_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+### Instruction:
+Translate the following text to Arabic.
+### Input:
+{text}
+### Response:
+"""
+eg_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+### Instruction:
+Translate the following text to Egyptian Arabic.
+### Input:
+{text}
+### Response:
+"""
+text = """Some habits are known as "keystone habits," and these influence the formation of other habits. \
+For example, identifying as the type of person who takes care of their body and is in the habit of exercising regularly, \
+can also influence eating better and using credit cards less. In business, \
+safety can be a keystone habit that influences other habits that result in greater productivity.[17]"""
+ar_text = pipe(ar_template.format(text=text),
+               max_new_tokens=256,
+               do_sample=True,
+               temperature=0.3,
+               top_p=0.5)
+eg_text = pipe(eg_template.format(text=ar_text),
+               max_new_tokens=256,
+               do_sample=True,
+               temperature=0.3,
+               top_p=0.5)
+print("Original Text:" text)
+print("\nArabic Translation:", ar_text)
+print("\nEgyptian Arabic Translation:", eg_text)
+```
+## Training and evaluation data
+[ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/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