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Text2Text Generation
Transformers
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Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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End of training

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  1. README.md +58 -0
  2. config.json +32 -0
  3. generation_config.json +7 -0
  4. model.safetensors +3 -0
  5. runs/Feb26_06-29-29_n10v61og1x/events.out.tfevents.1708928970.n10v61og1x.98.0 +3 -0
  6. runs/Feb26_06-30-22_n10v61og1x/events.out.tfevents.1708929022.n10v61og1x.157.0 +3 -0
  7. runs/Feb26_06-31-13_n10v61og1x/events.out.tfevents.1708929073.n10v61og1x.213.0 +3 -0
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  9. runs/Feb26_06-45-10_n10v61og1x/events.out.tfevents.1708929911.n10v61og1x.333.0 +3 -0
  10. runs/Feb26_06-45-10_n10v61og1x/events.out.tfevents.1708940531.n10v61og1x.333.1 +3 -0
  11. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: gaussalgo/T5-LM-Large-text2sql-spider
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: results
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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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+ # results
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+
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+ This model is a fine-tuned version of [gaussalgo/T5-LM-Large-text2sql-spider](https://huggingface.co/gaussalgo/T5-LM-Large-text2sql-spider) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0163
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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: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 1
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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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.0297 | 1.0 | 1900 | 0.0213 |
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+ | 0.0204 | 2.0 | 3800 | 0.0176 |
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+ | 0.0148 | 3.0 | 5700 | 0.0163 |
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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 2.2.1+cu121
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+ - Datasets 2.4.0
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+ - Tokenizers 0.15.2
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "classifier_dropout": 0.0,
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+ "d_ff": 2816,
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+ "d_kv": 64,
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+ "d_model": 1024,
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+ "decoder_start_token_id": 0,
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+ "dense_act_fn": "gelu_new",
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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+ "feed_forward_proj": "gated-gelu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "is_gated_act": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "num_decoder_layers": 24,
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+ "num_heads": 16,
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+ "num_layers": 24,
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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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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.1",
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
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