Training complete!

README.md

@@ -1,36 +1,55 @@
-
 ---
+base_model: google/t5-efficient-tiny
+library_name: peft
+license: apache-2.0
 tags:
-- autotrain
-- text2text-generation
-base_model: google/t5-efficient-tiny-nh8
-widget:
-- text: "I love AutoTrain"
-datasets:
-- gizemgg/wiki-eng-summary-trial-gen0-transformed-instruction
+- generated_from_trainer
+model-index:
+- name: t5-efficient-tiny-nh8-summarizer
+  results: []
 ---
 
-# Model Trained Using AutoTrain
+<!-- 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. -->
+
+# t5-efficient-tiny-nh8-summarizer
+
+This model is a fine-tuned version of [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on an unknown dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
 
-- Problem type: Seq2Seq
+More information needed
 
-## Validation Metrics
-loss: 2.225323438644409
+## Training and evaluation data
 
-rouge1: 26.024
+More information needed
 
-rouge2: 24.1663
+## Training procedure
 
-rougeL: 25.432
+### Training hyperparameters
 
-rougeLsum: 25.9929
+The following hyperparameters were used during training:
+- learning_rate: 7.000000000000001e-05
+- train_batch_size: 10
+- eval_batch_size: 10
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
 
-gen_len: 18.8
+### Training results
 
-runtime: 56.5847
 
-samples_per_second: 7.246
 
-steps_per_second: 1.82
+### Framework versions
 
-: 3.0
+- PEFT 0.14.0
+- Transformers 4.47.0
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.21.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "T5ForConditionalGeneration",
+    "parent_library": "transformers.models.t5.modeling_t5"
+  },
+  "base_model_name_or_path": "google/t5-efficient-tiny",
+  "bias": "none",
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q",
+    "v"
+  ],
+  "task_type": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 793064

training_args.bin

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