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multi-e5-base_lmd-comments_v1

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  1. README.md +110 -0
  2. config.json +39 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: intfloat/multilingual-e5-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: multi-e5-base_lmd-comments_v1
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+ results: []
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+ ---
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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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+
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+ # multi-e5-base_lmd-comments_v1
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+
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+ This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6013
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+ - F1: 0.8539
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+ - Accuracy: 0.8505
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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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: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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+ | 1.0859 | 0.04 | 100 | 1.0531 | 0.6574 | 0.6716 |
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+ | 0.9993 | 0.08 | 200 | 0.8669 | 0.7260 | 0.7266 |
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+ | 0.7514 | 0.12 | 300 | 0.7077 | 0.7582 | 0.7699 |
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+ | 0.6928 | 0.17 | 400 | 0.8825 | 0.7521 | 0.7856 |
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+ | 0.6349 | 0.21 | 500 | 0.6178 | 0.7947 | 0.7778 |
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+ | 0.5939 | 0.25 | 600 | 0.6509 | 0.7977 | 0.7847 |
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+ | 0.6461 | 0.29 | 700 | 0.5820 | 0.7951 | 0.7778 |
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+ | 0.5346 | 0.33 | 800 | 0.7509 | 0.8022 | 0.8014 |
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+ | 0.622 | 0.37 | 900 | 0.8165 | 0.7902 | 0.7935 |
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+ | 0.6124 | 0.41 | 1000 | 0.6754 | 0.7885 | 0.7788 |
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+ | 0.6285 | 0.46 | 1100 | 0.5179 | 0.8284 | 0.8210 |
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+ | 0.5838 | 0.5 | 1200 | 0.5335 | 0.8149 | 0.8024 |
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+ | 0.6116 | 0.54 | 1300 | 0.5584 | 0.8301 | 0.8240 |
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+ | 0.5578 | 0.58 | 1400 | 0.6135 | 0.7670 | 0.7404 |
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+ | 0.534 | 0.62 | 1500 | 0.6407 | 0.8153 | 0.8063 |
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+ | 0.5343 | 0.66 | 1600 | 0.5500 | 0.8381 | 0.8279 |
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+ | 0.5575 | 0.7 | 1700 | 0.6355 | 0.8170 | 0.8102 |
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+ | 0.5961 | 0.75 | 1800 | 0.5465 | 0.8450 | 0.8446 |
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+ | 0.5623 | 0.79 | 1900 | 0.5787 | 0.7875 | 0.7719 |
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+ | 0.5436 | 0.83 | 2000 | 0.6035 | 0.8494 | 0.8525 |
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+ | 0.5662 | 0.87 | 2100 | 0.4979 | 0.8210 | 0.8083 |
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+ | 0.5227 | 0.91 | 2200 | 0.6157 | 0.8320 | 0.8328 |
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+ | 0.557 | 0.95 | 2300 | 0.5721 | 0.8488 | 0.8505 |
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+ | 0.5369 | 0.99 | 2400 | 0.5191 | 0.8222 | 0.8112 |
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+ | 0.4846 | 1.04 | 2500 | 0.4966 | 0.8304 | 0.8201 |
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+ | 0.4094 | 1.08 | 2600 | 0.6385 | 0.8368 | 0.8328 |
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+ | 0.4045 | 1.12 | 2700 | 0.6165 | 0.8476 | 0.8456 |
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+ | 0.4835 | 1.16 | 2800 | 0.6792 | 0.8536 | 0.8535 |
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+ | 0.3949 | 1.2 | 2900 | 0.7400 | 0.8559 | 0.8574 |
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+ | 0.4157 | 1.24 | 3000 | 0.6305 | 0.8319 | 0.8279 |
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+ | 0.4638 | 1.28 | 3100 | 0.5507 | 0.8438 | 0.8387 |
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+ | 0.4438 | 1.33 | 3200 | 0.5208 | 0.8426 | 0.8348 |
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+ | 0.4224 | 1.37 | 3300 | 0.6534 | 0.8330 | 0.8279 |
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+ | 0.4703 | 1.41 | 3400 | 0.6486 | 0.8456 | 0.8427 |
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+ | 0.4912 | 1.45 | 3500 | 0.6370 | 0.8544 | 0.8505 |
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+ | 0.4396 | 1.49 | 3600 | 0.6866 | 0.8520 | 0.8505 |
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+ | 0.437 | 1.53 | 3700 | 0.6436 | 0.8536 | 0.8505 |
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+ | 0.3993 | 1.57 | 3800 | 0.6910 | 0.8517 | 0.8515 |
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+ | 0.3712 | 1.62 | 3900 | 0.6449 | 0.8588 | 0.8564 |
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+ | 0.4156 | 1.66 | 4000 | 0.6478 | 0.8560 | 0.8535 |
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+ | 0.4564 | 1.7 | 4100 | 0.6475 | 0.8577 | 0.8555 |
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+ | 0.4273 | 1.74 | 4200 | 0.6044 | 0.8456 | 0.8397 |
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+ | 0.4284 | 1.78 | 4300 | 0.6219 | 0.8499 | 0.8466 |
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+ | 0.4466 | 1.82 | 4400 | 0.5871 | 0.8535 | 0.8496 |
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+ | 0.3932 | 1.86 | 4500 | 0.5940 | 0.8551 | 0.8515 |
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+ | 0.3848 | 1.91 | 4600 | 0.5995 | 0.8559 | 0.8525 |
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+ | 0.4337 | 1.95 | 4700 | 0.6023 | 0.8539 | 0.8505 |
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+ | 0.3991 | 1.99 | 4800 | 0.6013 | 0.8539 | 0.8505 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "intfloat/multilingual-e5-base",
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+ "architectures": [
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+ "XLMRobertaForSequenceClassification"
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+ ],
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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": "LABEL_0",
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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": "4.38.1",
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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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