
# DistilBERT fine-tuned for news classification

This model is based on [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medium, good).

## Training data

The dataset used to fine-tune the model is [news-small](https://huggingface.co/datasets/valurank/news-small), the 300 article news dataset manually annotated by Alex.

## Inputs

Similar to its base model, this model accepts inputs with a maximum length of 512 tokens.

{"language": "en", "license": "other", "datasets": ["valurank/news-small"]}
transformers pytorch distilbert text-classification en dataset:valurank/news-small license:other autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #en #dataset-valurank/news-small #license-other #autotrain_compatible #endpoints_compatible #region-us 


# DistilBERT fine-tuned for news classification

This model is based on distilbert-base-uncased pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medium, good).

## Training data

The dataset used to fine-tune the model is news-small, the 300 article news dataset manually annotated by Alex.

## Inputs

Similar to its base model, this model accepts inputs with a maximum length of 512 tokens.

# DistilBERT fine-tuned for news classification

This model is based on distilbert-base-uncased pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medium, good). ## Training data

The dataset used to fine-tune the model is news-small, the 300 article news dataset manually annotated by Alex. ## Inputs

Similar to its base model, this model accepts inputs with a maximum length of 512 tokens.
TAGS
#transformers #pytorch #distilbert #text-classification #en #dataset-valurank/news-small #license-other #autotrain_compatible #endpoints_compatible #region-us 
 # DistilBERT fine-tuned for news classification

This model is based on distilbert-base-uncased pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medium, good). ## Training data

The dataset used to fine-tune the model is news-small, the 300 article news dataset manually annotated by Alex. ## Inputs

Similar to its base model, this model accepts inputs with a maximum length of 512 tokens.
passage: TAGS
#transformers #pytorch #distilbert #text-classification #en #dataset-valurank/news-small #license-other #autotrain_compatible #endpoints_compatible #region-us 
# DistilBERT fine-tuned for news classification

This model is based on distilbert-base-uncased pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medium, good).## Training data

The dataset used to fine-tune the model is news-small, the 300 article news dataset manually annotated by Alex.## Inputs

Similar to its base model, this model accepts inputs with a maximum length of 512 tokens.