distilbert_token_itr0_1e-05_all_01_03_2022-14_33_33 Open-source Model - Efficiently Complete Text Classification Tasks

Distilbert Token Itr0 1e 05 All 01 03 2022 14 33 33

Developed by ali2066

This model is a fine-tuned version of DistilBERT on an unspecified dataset, primarily used for text classification tasks.

Large Language Model

Transformers

Open Source License:Apache-2.0 #Text Classification #High Accuracy #DistilBERT Fine-tuning

Downloads 15

Release Time : 3/2/2022

Model Overview

A fine-tuned model based on the DistilBERT architecture, suitable for text classification tasks with high accuracy and efficiency.

Model Features

Efficient Fine-tuning

Based on the DistilBERT architecture, the model reduces the number of parameters while maintaining high performance, improving training and inference efficiency.

Multi-metric Optimization

The model is optimized across multiple metrics including precision, recall, F1 score, and accuracy, making it suitable for applications requiring balanced performance.

Model Capabilities

Text Classification

Sentiment Analysis

Use Cases

Text Analysis

Sentiment Analysis

Used to analyze the sentiment tendency of text, such as positive or negative reviews.

Achieved an accuracy of 84.91% on the evaluation set.

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	30	0.4549	0.0228	0.0351	0.0276	0.7734
No log	2.0	60	0.3577	0.0814	0.1260	0.0989	0.8355
No log	3.0	90	0.3116	0.1534	0.2648	0.1943	0.8611
No log	4.0	120	0.2975	0.1792	0.2967	0.2234	0.8690
No log	5.0	150	0.2935	0.1873	0.2998	0.2305	0.8715

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Distilbert Token Itr0 1e 05 All 01 03 2022 14 33 33

Model Overview

Model Features

Model Capabilities

Use Cases

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Model description

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Training and evaluation data

Training procedure

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