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README.md

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 ---
 license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: finetuning-financial-news-sentiment
+  results: []
 ---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# finetuning-financial-news-sentiment
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3345
+- Accuracy: 0.8751
+- F1: 0.8751
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6

config.json

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+{"hidden_size": 128, "hidden_act": "gelu", "initializer_range": 0.02, "vocab_size": 30522, "hidden_dropout_prob": 0.1, "num_attention_heads": 2, "type_vocab_size": 2, "max_position_embeddings": 512, "num_hidden_layers": 2, "intermediate_size": 512, "attention_probs_dropout_prob": 0.1, "model_type": "bert"}

pytorch_model.bin

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