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Browse files- README.md +36 -0
- checkpoint-485/config.json +40 -0
- checkpoint-485/model.safetensors +3 -0
- checkpoint-485/optimizer.pt +3 -0
- checkpoint-485/rng_state.pth +3 -0
- checkpoint-485/scheduler.pt +3 -0
- checkpoint-485/trainer_state.json +200 -0
- checkpoint-485/training_args.bin +3 -0
- config.json +40 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- runs/Jan11_03-48-48_r-hanbrar-financial-bot2-70wmgxe8-4e0bf-pb72t/events.out.tfevents.1736567329.r-hanbrar-financial-bot2-70wmgxe8-4e0bf-pb72t.142.0 +2 -2
- runs/Jan11_03-48-48_r-hanbrar-financial-bot2-70wmgxe8-4e0bf-pb72t/events.out.tfevents.1736572840.r-hanbrar-financial-bot2-70wmgxe8-4e0bf-pb72t.142.1 +3 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +62 -0
- training_args.bin +3 -0
- training_params.json +30 -0
- vocab.json +0 -0
README.md
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---
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tags:
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- autotrain
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- text-classification
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base_model: mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis
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widget:
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- text: "I love AutoTrain"
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---
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# Model Trained Using AutoTrain
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- Problem type: Text Classification
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## Validation Metrics
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loss: 0.5204629898071289
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f1_macro: 0.8248638325526141
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f1_micro: 0.8391752577319588
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f1_weighted: 0.8401728559000128
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precision_macro: 0.8043237511636941
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precision_micro: 0.8391752577319588
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precision_weighted: 0.845019702890122
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recall_macro: 0.853526208639845
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recall_micro: 0.8391752577319588
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recall_weighted: 0.8391752577319588
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accuracy: 0.8391752577319588
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checkpoint-485/config.json
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"_name_or_path": "mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis",
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"_num_labels": 3,
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"hidden_size": 768,
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"id2label": {
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"0": "negative",
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"1": "neutral",
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"2": "positive"
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"layer_norm_eps": 1e-05,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.47.1",
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"type_vocab_size": 1,
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"use_cache": true,
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}
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checkpoint-485/optimizer.pt
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vocab.json
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