Text Generation
Transformers
Safetensors
English
blenderbot
text2text-generation
BlenderBot
Conversational
Fine-tuned
Text Generation
Eval Results (legacy)
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("12sciencejnv/TalkGPT")
model = AutoModelForSeq2SeqLM.from_pretrained("12sciencejnv/TalkGPT")Quick Links
TalkGPT
This model is a fine-tuned version of BlenderBot-400M (distilled) based on a custom conversational dataset. It is designed to generate conversational responses in English.
License
Apache 2.0
Datasets
The model is fine-tuned on a custom dataset consisting of conversational dialogues.
Language
English
Metrics
- BLEU: 0.1687 (calculated on the validation set)
- ROUGE-1: 0.4078
- ROUGE-2: 0.1912
- ROUGE-L: 0.3418
- ROUGE-Lsum: 0.3401
- Training Loss: 0.2460 (final training loss after fine-tuning)
Base Model
The model is based on the BlenderBot-400M-distill architecture by Facebook AI.
Pipeline Tag
text-generation
Library Name
transformers
Tags
BlenderBot, Conversational, Fine-tuned, Text Generation
Eval Results
The model achieved the following results on the validation set:
- BLEU: 0.1687
- ROUGE-1: 0.4078
- ROUGE-2: 0.1912
- ROUGE-L: 0.3418
- ROUGE-Lsum: 0.3401
- Training Loss: 0.2460 after 3 epochs of fine-tuning.
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Model tree for 12sciencejnv/TalkGPT
Base model
facebook/blenderbot-400M-distillEvaluation results
- BLEU on custom-datasetSelf-evaluated0.169
- ROUGE on custom-datasetSelf-evaluated[object Object]
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="12sciencejnv/TalkGPT")