# Pretrained model used for the NASDAQ_news dataset

## Model Info:

This model is a fine-tuned DistilBertForSequenceClassification on random samples of the NASDAQ_news dataset.
It uses the DistilBertTokenizerFast as a tokenizer.

### Model Data:

The model is finetuned on headlines
{}
transformers pytorch distilbert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

# Pretrained model used for the NASDAQ_news dataset

## Model Info:

This model is a fine-tuned DistilBertForSequenceClassification on random samples of the NASDAQ_news dataset.
It uses the DistilBertTokenizerFast as a tokenizer.

### Model Data:

The model is finetuned on headlines
# Pretrained model used for the NASDAQ_news dataset ## Model Info:

This model is a fine-tuned DistilBertForSequenceClassification on random samples of the NASDAQ_news dataset.
It uses the DistilBertTokenizerFast as a tokenizer. ### Model Data:

The model is finetuned on headlines
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
 # Pretrained model used for the NASDAQ_news dataset ## Model Info:

This model is a fine-tuned DistilBertForSequenceClassification on random samples of the NASDAQ_news dataset.
It uses the DistilBertTokenizerFast as a tokenizer. ### Model Data:

The model is finetuned on headlines
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
# Pretrained model used for the NASDAQ_news dataset## Model Info:

This model is a fine-tuned DistilBertForSequenceClassification on random samples of the NASDAQ_news dataset.
It uses the DistilBertTokenizerFast as a tokenizer.### Model Data:

The model is finetuned on headlines