t5-large_PREFIX_TUNING_SEQ2SEQ_EMOTION

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+base_model: t5-large
+model-index:
+- name: output_emotion
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# output_emotion
+
+This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.9008
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 7.3148        | 2.0   | 1800 | 6.9641          |
+| 7.243         | 4.0   | 3600 | 6.9008          |
+
+
+### Framework versions
+
+- PEFT 0.7.1
+- Transformers 4.36.2
+- Pytorch 2.0.0
+- Datasets 2.15.0
+- Tokenizers 0.15.0

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "t5-large",
+  "encoder_hidden_size": 1024,
+  "inference_mode": true,
+  "num_attention_heads": 16,
+  "num_layers": 24,
+  "num_transformer_submodules": 2,
+  "num_virtual_tokens": 20,
+  "peft_type": "PREFIX_TUNING",
+  "prefix_projection": false,
+  "revision": null,
+  "task_type": "SEQ_2_SEQ_LM",
+  "token_dim": 1024
+}

adapter_model.safetensors

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+size 3932288

training_args.bin

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