Training complete!

README.md

@@ -1,7 +1,7 @@
 ---
-base_model: google/t5-efficient-tiny
-library_name: peft
+library_name: transformers
 license: apache-2.0
+base_model: google/t5-efficient-tiny-nh8
 tags:
 - generated_from_trainer
 model-index:
@@ -14,7 +14,14 @@ 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.
+This model is a fine-tuned version of [google/t5-efficient-tiny-nh8](https://huggingface.co/google/t5-efficient-tiny-nh8) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 6.4709
+- eval_model_preparation_time: 0.0027
+- eval_runtime: 0.8703
+- eval_samples_per_second: 114.907
+- eval_steps_per_second: 17.236
+- step: 0
 
 ## Model description
 
@@ -34,22 +41,17 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 7.000000000000001e-05
-- train_batch_size: 10
-- eval_batch_size: 10
+- train_batch_size: 7
+- eval_batch_size: 7
 - 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
 
-### Training results
-
-
-
 ### Framework versions
 
-- PEFT 0.14.0
 - Transformers 4.47.0
 - Pytorch 2.4.0+cu121
 - Datasets 3.0.0
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0

config.json

@@ -25,7 +25,7 @@
   "relative_attention_max_distance": 128,
   "relative_attention_num_buckets": 32,
   "torch_dtype": "float32",
-  "transformers_version": "4.46.2",
+  "transformers_version": "4.47.0",
   "use_cache": true,
   "vocab_size": 32128
 }

generation_config.json

@@ -1,6 +1,7 @@
 {
+  "_from_model_config": true,
   "decoder_start_token_id": 0,
   "eos_token_id": 1,
   "pad_token_id": 0,
-  "transformers_version": "4.46.2"
+  "transformers_version": "4.47.0"
 }

model.safetensors

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training_args.bin

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