Model save

README.md

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+---
+license: apache-2.0
+base_model: google/mt5-small
+tags:
+- generated_from_trainer
+model-index:
+- name: mt5-small-amharic-text-summaization
+  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. -->
+
+# mt5-small-amharic-text-summaization
+
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 1.9166
+- eval_rouge1: 17.2202
+- eval_rouge2: 9.6515
+- eval_rougeL: 16.8757
+- eval_rougeLsum: 16.8802
+- eval_runtime: 191.4842
+- eval_samples_per_second: 14.043
+- eval_steps_per_second: 1.76
+- epoch: 10.0
+- step: 13450
+
+## 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: 5.6e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 12
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

generation_config.json

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+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.35.2"
+}

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