End of training
Browse files- .gitattributes +1 -0
- README.md +75 -0
- config.json +46 -0
- fasttext_model.bin +3 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
- vocab.txt +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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vocab.txt filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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base_model: google-bert/bert-base-multilingual-uncased
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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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- precision
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- recall
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- f1
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model-index:
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- name: nlp_1
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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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# nlp_1
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4215
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- Accuracy: 0.9037
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- Precision: 0.8944
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- Recall: 0.9025
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- F1: 0.8968
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.3252 | 1.0 | 48 | 0.4194 | 0.8670 | 0.8671 | 0.8619 | 0.8617 |
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| 0.1803 | 2.0 | 96 | 0.3779 | 0.8853 | 0.8807 | 0.8788 | 0.8773 |
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| 0.1713 | 3.0 | 144 | 0.4097 | 0.8945 | 0.8864 | 0.8924 | 0.8857 |
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| 0.1359 | 4.0 | 192 | 0.4012 | 0.8945 | 0.8919 | 0.8841 | 0.8873 |
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| 0.1201 | 5.0 | 240 | 0.3770 | 0.8899 | 0.8809 | 0.8876 | 0.8818 |
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| 0.0735 | 6.0 | 288 | 0.4204 | 0.8991 | 0.8934 | 0.8975 | 0.8921 |
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| 0.0807 | 7.0 | 336 | 0.4092 | 0.9083 | 0.9059 | 0.9020 | 0.9024 |
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| 0.1066 | 8.0 | 384 | 0.4181 | 0.8991 | 0.8894 | 0.8928 | 0.8903 |
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| 0.0615 | 9.0 | 432 | 0.4212 | 0.9083 | 0.8988 | 0.9066 | 0.9014 |
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| 0.071 | 10.0 | 480 | 0.4215 | 0.9037 | 0.8944 | 0.9025 | 0.8968 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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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": "google-bert/bert-base-multilingual-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"directionality": "bidi",
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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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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4"
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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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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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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": "4.42.4",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 548133
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}
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fasttext_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:317f9c97ba6d378db51a433c6180c5cafe0e4f93fb6ac7d97fddfbaecce37e30
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size 9534119835
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ba5834cce8eb05ab05a8dc6f9c306a4a85fe78d961ece9d5986d3545cdb0333f
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size 2028069268
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3911806d1f4d18201c7390359eaaa542811cd4ccacfaf7c504690b0867ab95c
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size 5048
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vocab.txt
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version https://git-lfs.github.com/spec/v1
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size 17457360
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