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README.md

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+---
+license: gemma
+base_model: google/gemma-7b
+tags:
+- alignment-handbook
+- trl
+- sft
+- generated_from_trainer
+- trl
+- sft
+- generated_from_trainer
+datasets:
+- masakhane/african-translated-alpaca
+model-index:
+- name: zephyr-7b-gemma-sft-african-alpaca
+  results: []
+language:
+- af
+- am
+- ar
+- en
+- ee
+---
+
+<!-- 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. -->
+
+# zephyr-7b-gemma-sft-alpaca
+
+This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the masakhane/african-translated-alpaca dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2737
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- total_eval_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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 0.8671        | 1.0   | 5882  | 0.7445          |
+| 0.5235        | 2.0   | 11764 | 0.3905          |
+| 0.3309        | 3.0   | 17646 | 0.2737          |
+
+
+### Framework versions
+
+- Transformers 4.39.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.14.6
+- Tokenizers 0.15.2
+
+
+
+
+### Usage
+
+```python
+
+# Install transformers from source - only needed for versions <= v4.34
+# pip install git+https://github.com/huggingface/transformers.git
+# pip install accelerate
+
+import torch
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="masakhane/zephyr-7b-gemma-sft-african-alpaca", torch_dtype=torch.bfloat16, device_map="auto")
+
+# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
+messages = [
+    {
+        "role": "system",
+        "content": "You are a friendly chatbot who answewrs question in given language",
+    },
+    {"role": "user", "content": "what is the 3 biggest countrys in Africa?"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+# <|system|>
+# You are a friendly chatbot who always responds in the style of a pirate<eos>
+# <|user|>
+# what is the 3 biggest countrys in Africa?<eos>
+# <|assistant|>
+# The 3 biggest countries in Africa are Nigeria, Ethiopia and South Africa.
+```
+
+
+### Quantized Versions through bitsandbytes
+
+``` python
+
+import torch
+from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+
+quantization_config = BitsAndBytesConfig(load_in_4bit=True)
+
+tokenizer = AutoTokenizer.from_pretrained("masakhane/zephyr-7b-gemma-sft-african-alpaca")
+model = AutoModelForCausalLM.from_pretrained("masakhane/zephyr-7b-gemma-sft-african-alpaca", quantization_config=quantization_config)
+
+
+pipe = pipeline("text-generation", model=model,tokenizer=tokenizer, torch_dtype=torch.bfloat16, device_map="auto")
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a friendly chatbot who answewrs question in given language",
+    },
+    {"role": "user", "content": "list languages in Africa?"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+
+```

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_loss": 0.273702472448349,
+    "eval_runtime": 75.0151,
+    "eval_samples": 4600,
+    "eval_samples_per_second": 4.826,
+    "eval_steps_per_second": 0.613,
+    "train_loss": 0.7695021375204772,
+    "train_runtime": 155405.9935,
+    "train_samples": 1196046,
+    "train_samples_per_second": 1.817,
+    "train_steps_per_second": 0.114
+}

config.json

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+{
+  "_name_or_path": "google/gemma-7b",
+  "architectures": [
+    "GemmaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "head_dim": 256,
+  "hidden_act": "gelu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 24576,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 16,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.0.dev0",
+  "use_cache": true,
+  "vocab_size": 256000
+}

eval_results.json

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+{
+    "epoch": 3.0,
+    "eval_loss": 0.273702472448349,
+    "eval_runtime": 75.0151,
+    "eval_samples": 4600,
+    "eval_samples_per_second": 4.826,
+    "eval_steps_per_second": 0.613
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.39.0.dev0"
+}

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