CatBarks/t5_es_BCE_weight_4_2
Browse files- README.md +78 -0
- config.json +63 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: google-t5/t5-base
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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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- f1
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model-index:
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- name: t5_es_weight_4_2
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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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# t5_es_weight_4_2
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0201
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- Accuracy: 0.9955
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- F1: 0.9958
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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: 0.0001
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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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- gradient_accumulation_steps: 64
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- total_train_batch_size: 4096
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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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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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| 0.7207 | 6.8817 | 50 | 0.6639 | 0.631 | 0.7122 |
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| 0.6227 | 13.7634 | 100 | 0.4261 | 0.8935 | 0.9021 |
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| 0.2336 | 20.6452 | 150 | 0.0745 | 0.979 | 0.9803 |
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| 0.0593 | 27.5269 | 200 | 0.0453 | 0.9845 | 0.9853 |
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| 0.0286 | 34.4086 | 250 | 0.0287 | 0.9915 | 0.992 |
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| 0.0149 | 41.2903 | 300 | 0.0201 | 0.995 | 0.9953 |
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| 0.0078 | 48.1720 | 350 | 0.0194 | 0.996 | 0.9962 |
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| 0.0047 | 55.0538 | 400 | 0.0203 | 0.9965 | 0.9967 |
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| 0.0033 | 61.9355 | 450 | 0.0203 | 0.996 | 0.9962 |
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| 0.0024 | 68.8172 | 500 | 0.0192 | 0.996 | 0.9962 |
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| 0.0016 | 75.6989 | 550 | 0.0194 | 0.996 | 0.9962 |
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| 0.0008 | 82.5806 | 600 | 0.0219 | 0.996 | 0.9962 |
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| 0.0008 | 89.4624 | 650 | 0.0249 | 0.996 | 0.9963 |
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| 0.0026 | 96.3441 | 700 | 0.0201 | 0.9955 | 0.9958 |
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### Framework versions
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- Transformers 4.40.0
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- Pytorch 2.4.1+cu121
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- Datasets 3.1.0
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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-t5/t5-base",
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"architectures": [
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"T5ForSequenceClassification"
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],
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"classifier_dropout": 0.0,
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"d_ff": 3072,
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"d_kv": 64,
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"d_model": 768,
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"decoder_start_token_id": 0,
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"dense_act_fn": "relu",
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "relu",
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"is_gated_act": false,
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"layer_norm_epsilon": 1e-06,
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"model_type": "t5",
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"n_positions": 512,
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"num_decoder_layers": 12,
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"num_heads": 12,
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"num_layers": 12,
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"output_hidden_states": true,
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"output_past": true,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"relative_attention_max_distance": 128,
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"relative_attention_num_buckets": 32,
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"task_specific_params": {
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"summarization": {
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"early_stopping": true,
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"length_penalty": 2.0,
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"max_length": 200,
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"min_length": 30,
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"no_repeat_ngram_size": 3,
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"num_beams": 4,
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"prefix": "summarize: "
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},
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"translation_en_to_de": {
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"early_stopping": true,
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"max_length": 300,
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"num_beams": 4,
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"prefix": "translate English to German: "
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},
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"translation_en_to_fr": {
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"early_stopping": true,
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"max_length": 300,
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"num_beams": 4,
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"prefix": "translate English to French: "
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},
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"translation_en_to_ro": {
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"early_stopping": true,
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"max_length": 300,
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"num_beams": 4,
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"prefix": "translate English to Romanian: "
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}
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},
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"torch_dtype": "float32",
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"transformers_version": "4.40.0",
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"use_cache": true,
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"vocab_size": 32128
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:af366971309dc6c241c6a9d99ffdf637570caa1b149fc52aa4f1668e7e237849
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size 894016712
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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:faa150d7417524857cc70e5a5a7679365fe7af80e2c6f51e8a7c9c1c998c1177
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size 4984
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