Question Answering
Transformers
TensorBoard
Safetensors
gemma
text-generation
trl
sft
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("IvanD2002/gemma-chatbot")
model = AutoModelForCausalLM.from_pretrained("IvanD2002/gemma-chatbot")Quick Links
gemma-chatbot
This model is a fine-tuned version of google/gemma-2b-it on the None dataset.
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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 250
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
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Model tree for IvanD2002/gemma-chatbot
Base model
google/gemma-2b-it
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="IvanD2002/gemma-chatbot")