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davidgaofc
/
TechDebtLabeler

Text2Text Generation
Transformers
TensorBoard
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Metrics Community
davidgaofc commited on
Commit
3467548
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1 Parent(s): 0215c56

End of training

Browse files
Files changed (22) hide show
  1. README.md +55 -0
  2. config.json +69 -0
  3. generation_config.json +8 -0
  4. merges.txt +0 -0
  5. model.safetensors +3 -0
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  19. tokenizer.json +0 -0
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  22. vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: Salesforce/codet5-small
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: training
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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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+ # training
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+
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+ This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on an unknown dataset.
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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: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 100
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+ - total_train_batch_size: 100
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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: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ {
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+ "_name_or_path": "Salesforce/codet5-small",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "bos_token_id": 1,
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+ "classifier_dropout": 0.0,
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+ "d_ff": 2048,
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+ "d_kv": 64,
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+ "dense_act_fn": "relu",
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "LABEL_0": 0
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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": 6,
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+ "num_heads": 8,
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+ "num_layers": 6,
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+ "output_past": true,
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+ "pad_token_id": 0,
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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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+ "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": "4.35.0",
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+ "use_cache": true,
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+ "vocab_size": 32100
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+ }
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