Ali Safaya
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Browse files- README.md +91 -3
- config.json +29 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
README.md
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---
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license:
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-
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- mlsum
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metrics:
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- rouge
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model-index:
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- name: eval-mt5-base-aggressive
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results:
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- task:
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name: Summarization
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type: summarization
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dataset:
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name: mlsum tu
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type: mlsum
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args: tu
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metrics:
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- name: Rouge1
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type: rouge
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value: 47.4222
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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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# eval-mt5-base-aggressive
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the mlsum tu dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.7801
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- Rouge1: 47.4222
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- Rouge2: 34.8624
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- Rougel: 42.2487
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- Rougelsum: 43.9494
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- Gen Len: 51.3525
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 2
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- total_eval_batch_size: 32
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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: 10.0
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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| 3.084 | 1.0 | 3895 | 2.9282 | 31.6872 | 22.1113 | 29.2851 | 29.7608 | 18.9861 |
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| 2.9162 | 2.0 | 7790 | 2.8552 | 32.1716 | 22.5001 | 29.6845 | 30.1887 | 18.9938 |
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| 2.8149 | 3.0 | 11685 | 2.8089 | 32.5681 | 22.689 | 30.0409 | 30.5507 | 18.9959 |
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| 2.7325 | 4.0 | 15580 | 2.7948 | 33.1236 | 23.1775 | 30.5156 | 31.0461 | 18.9958 |
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| 2.6679 | 5.0 | 19475 | 2.7810 | 33.1766 | 23.162 | 30.4802 | 31.0527 | 18.9967 |
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| 2.6237 | 6.0 | 23370 | 2.7790 | 33.1118 | 23.2043 | 30.5064 | 31.0096 | 18.9978 |
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| 2.5711 | 7.0 | 27265 | 2.7801 | 33.2033 | 23.2957 | 30.59 | 31.1504 | 18.9979 |
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| 2.538 | 8.0 | 31160 | 2.7777 | 33.0256 | 23.0621 | 30.3818 | 30.978 | 18.998 |
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| 2.5 | 9.0 | 35055 | 2.7839 | 33.2288 | 23.2361 | 30.5421 | 31.1573 | 18.998 |
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| 2.4719 | 10.0 | 38950 | 2.7832 | 33.2098 | 23.2274 | 30.5164 | 31.1094 | 18.9981 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.8.2+cu111
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- Datasets 1.14.0
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- Tokenizers 0.10.3
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config.json
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{
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"_name_or_path": "google/mt5-base",
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"architectures": [
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"MT5ForConditionalGeneration"
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],
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"d_ff": 2048,
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"d_kv": 64,
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"d_model": 768,
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"decoder_start_token_id": 0,
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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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"layer_norm_epsilon": 1e-06,
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"model_type": "mt5",
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"num_decoder_layers": 12,
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"num_heads": 12,
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"num_layers": 12,
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"output_past": true,
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"pad_token_id": 0,
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.11.3",
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"use_cache": true,
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"vocab_size": 250100
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:18b608a7836e1e81f15b72d9bbd255919547dbb21b035c9cf0abcad95e4fc8f2
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size 2329633625
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special_tokens_map.json
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{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
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size 4309802
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tokenizer.json
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tokenizer_config.json
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{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "extra_ids": 0, "additional_special_tokens": null, "special_tokens_map_file": "/home/patrick/.cache/torch/transformers/685ac0ca8568ec593a48b61b0a3c272beee9bc194a3c7241d15dcadb5f875e53.f76030f3ec1b96a8199b2593390c610e76ca8028ef3d24680000619ffb646276", "name_or_path": "google/mt5-base", "sp_model_kwargs": {}, "tokenizer_class": "T5Tokenizer"}
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