Training in progress, epoch 1
Browse files- .gitattributes +1 -0
- README.md +99 -0
- config.json +63 -0
- model.safetensors +3 -0
- runs/May25_22-14-38_Precision-3660/events.out.tfevents.1716639279.Precision-3660.1574450.0 +3 -0
- runs/May25_22-54-42_Precision-3660/events.out.tfevents.1716641682.Precision-3660.1584143.0 +3 -0
- runs/May25_23-26-39_Precision-3660/events.out.tfevents.1716643600.Precision-3660.1589267.0 +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +3 -0
- tokenizer_config.json +54 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: mit
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base_model: microsoft/Multilingual-MiniLM-L12-H384
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: intent_trading
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# intent_trading
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This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1741
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- Accuracy: 0.9548
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 40
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 227 | 1.5904 | 0.7689 |
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| No log | 2.0 | 454 | 1.0086 | 0.8670 |
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| 1.6528 | 3.0 | 681 | 0.6706 | 0.9055 |
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| 1.6528 | 4.0 | 908 | 0.4376 | 0.9518 |
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| 0.6124 | 5.0 | 1135 | 0.2966 | 0.9551 |
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| 0.6124 | 6.0 | 1362 | 0.2373 | 0.9504 |
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| 0.2536 | 7.0 | 1589 | 0.1967 | 0.9537 |
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| 0.2536 | 8.0 | 1816 | 0.1666 | 0.9565 |
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| 0.1476 | 9.0 | 2043 | 0.1642 | 0.9543 |
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| 0.1476 | 10.0 | 2270 | 0.1570 | 0.9551 |
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| 0.1476 | 11.0 | 2497 | 0.1500 | 0.9543 |
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| 0.1067 | 12.0 | 2724 | 0.1469 | 0.9548 |
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| 0.1067 | 13.0 | 2951 | 0.1458 | 0.9557 |
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| 0.0817 | 14.0 | 3178 | 0.1409 | 0.9540 |
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| 0.0817 | 15.0 | 3405 | 0.1426 | 0.9595 |
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| 0.0709 | 16.0 | 3632 | 0.1418 | 0.9540 |
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| 0.0709 | 17.0 | 3859 | 0.1416 | 0.9557 |
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| 0.0631 | 18.0 | 4086 | 0.1373 | 0.9581 |
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| 0.0631 | 19.0 | 4313 | 0.1458 | 0.9559 |
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| 0.0557 | 20.0 | 4540 | 0.1391 | 0.9559 |
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| 0.0557 | 21.0 | 4767 | 0.1526 | 0.9518 |
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| 0.0557 | 22.0 | 4994 | 0.1511 | 0.9529 |
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| 0.0495 | 23.0 | 5221 | 0.1578 | 0.9526 |
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| 0.0495 | 24.0 | 5448 | 0.1360 | 0.9568 |
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| 0.0443 | 25.0 | 5675 | 0.1451 | 0.9565 |
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| 0.0443 | 26.0 | 5902 | 0.1477 | 0.9562 |
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| 0.0419 | 27.0 | 6129 | 0.1624 | 0.9540 |
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| 0.0419 | 28.0 | 6356 | 0.1659 | 0.9537 |
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| 0.0371 | 29.0 | 6583 | 0.1607 | 0.9548 |
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| 0.0371 | 30.0 | 6810 | 0.1638 | 0.9543 |
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| 0.035 | 31.0 | 7037 | 0.1655 | 0.9529 |
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| 0.035 | 32.0 | 7264 | 0.1662 | 0.9562 |
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| 0.035 | 33.0 | 7491 | 0.1702 | 0.9532 |
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| 0.033 | 34.0 | 7718 | 0.1662 | 0.9562 |
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| 0.033 | 35.0 | 7945 | 0.1667 | 0.9532 |
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| 0.0309 | 36.0 | 8172 | 0.1794 | 0.9554 |
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| 0.0309 | 37.0 | 8399 | 0.1756 | 0.9546 |
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| 0.0292 | 38.0 | 8626 | 0.1722 | 0.9559 |
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| 0.0292 | 39.0 | 8853 | 0.1706 | 0.9559 |
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| 0.0281 | 40.0 | 9080 | 0.1741 | 0.9548 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.5
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "xlm-roberta-base",
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "buy_coin",
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"1": "sell_coin",
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"2": "current_coin_price",
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"3": "predict_signal",
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"4": "check_human",
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"5": "affirm",
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"6": "deny",
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"7": "goodbye",
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"8": "greet",
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"9": "inform",
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"10": "thankyou",
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"11": "help",
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"12": "human_handoff",
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"13": "out_of_scope",
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"14": "check_image"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"affirm": 5,
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"buy_coin": 0,
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"check_human": 4,
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"check_image": 14,
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"current_coin_price": 2,
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"deny": 6,
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"goodbye": 7,
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"greet": 8,
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"help": 11,
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"human_handoff": 12,
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"inform": 9,
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"out_of_scope": 13,
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"predict_signal": 3,
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"sell_coin": 1,
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"thankyou": 10
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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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": "4.40.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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model.safetensors
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runs/May25_22-14-38_Precision-3660/events.out.tfevents.1716639279.Precision-3660.1574450.0
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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