Distilroberta-base-testingSB - An open-source text processing model free for various text processing tasks

Distilroberta Base Testingsb Testingsb

Developed by MistahCase

This model is a fine-tuned version of distilroberta-base on an unknown dataset, primarily used for text processing tasks.

Large Language Model

Transformers

Open Source License:Apache-2.0 #Lightweight RoBERTa #Text fine-tuning optimization #Efficient training with low resources

Downloads 30

Release Time : 3/2/2022

Model Overview

This is a fine-tuned model based on DistilRoBERTa-base, suitable for general natural language processing tasks. The model was trained for 3 epochs and achieved a loss value of 0.9870 on the evaluation set.

Model Features

Efficient Fine-tuning

Fine-tuned based on the DistilRoBERTa-base model, retaining the original model's performance while adapting to specific tasks.

Lightweight

As a Distil version, it has a smaller size and faster inference speed compared to the full RoBERTa model.

Optimized Training

After 3 epochs of training, the validation loss decreased from 1.1171 to 0.9870, demonstrating good optimization results.

Model Capabilities

Text classification

Text understanding

Feature extraction

Use Cases

Text Analysis

Sentiment Analysis

Can be used to analyze the sentiment tendency of text.

Content Classification

Classify text content for processing.

Training Loss	Epoch	Step	Validation Loss
1.1463	1.0	1461	1.1171
1.0188	2.0	2922	1.0221
1.0016	3.0	4383	0.9870

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Distilroberta Base Testingsb Testingsb

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 distilroberta-base-testingSB-testingSB

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

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