End of training
Browse files- README.md +20 -5
- all_results.json +16 -0
- eval_results.json +10 -0
- train_results.json +9 -0
- trainer_state.json +830 -0
README.md
CHANGED
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---
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license: apache-2.0
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base_model: google/mt5-small
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tags:
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- generated_from_trainer
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metrics:
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- bleu
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model-index:
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- name: ft-wmt14-5
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-
results:
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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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@@ -15,11 +30,11 @@ should probably proofread and complete it, then remove this comment. -->
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# ft-wmt14-5
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-
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Bleu: 20.
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- Gen Len: 30.
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## Model description
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---
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language:
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- de
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- en
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license: apache-2.0
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base_model: google/mt5-small
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tags:
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- generated_from_trainer
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datasets:
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- lilferrit/wmt14-short
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metrics:
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- bleu
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model-index:
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- name: ft-wmt14-5
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results:
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- task:
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name: Translation
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type: translation
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dataset:
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name: lilferrit/wmt14-short
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type: lilferrit/wmt14-short
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metrics:
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- name: Bleu
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type: bleu
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value: 20.7584
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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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# ft-wmt14-5
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+
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the lilferrit/wmt14-short dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0604
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- Bleu: 20.7584
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- Gen Len: 30.499
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## Model description
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all_results.json
ADDED
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{
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"epoch": 2.7777777777777777,
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"eval_bleu": 20.7584,
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"eval_gen_len": 30.499,
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"eval_loss": 2.0603742599487305,
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"eval_runtime": 371.1712,
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"eval_samples": 3000,
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"eval_samples_per_second": 8.083,
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"eval_steps_per_second": 1.01,
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"total_flos": 1.4240580791795712e+17,
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"train_loss": 0.5475473999023438,
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"train_runtime": 14821.2356,
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"train_samples": 576000,
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"train_samples_per_second": 107.953,
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"train_steps_per_second": 6.747
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}
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eval_results.json
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{
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"epoch": 2.7777777777777777,
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"eval_bleu": 20.7584,
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"eval_gen_len": 30.499,
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"eval_loss": 2.0603742599487305,
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"eval_runtime": 371.1712,
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"eval_samples": 3000,
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"eval_samples_per_second": 8.083,
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"eval_steps_per_second": 1.01
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}
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train_results.json
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{
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"epoch": 2.7777777777777777,
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"total_flos": 1.4240580791795712e+17,
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"train_loss": 0.5475473999023438,
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"train_runtime": 14821.2356,
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"train_samples": 576000,
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"train_samples_per_second": 107.953,
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"train_steps_per_second": 6.747
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}
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trainer_state.json
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|
1 |
+
{
|
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+
"best_metric": 20.7584,
|
3 |
+
"best_model_checkpoint": "/local1/hfs/gs_stuff/ft-wmt14-5/checkpoint-90000",
|
4 |
+
"epoch": 2.7777777777777777,
|
5 |
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"eval_steps": 10000,
|
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"global_step": 100000,
|
7 |
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"is_hyper_param_search": false,
|
8 |
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"is_local_process_zero": true,
|
9 |
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"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
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{
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"epoch": 0.027777777777777776,
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"grad_norm": 1.9314790964126587,
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"learning_rate": 0.0005,
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"loss": 3.3589,
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"step": 1000
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},
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{
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"epoch": 0.05555555555555555,
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"grad_norm": 1.7348469495773315,
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"learning_rate": 0.0005,
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"loss": 2.5263,
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"step": 2000
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},
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{
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"epoch": 0.08333333333333333,
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"grad_norm": 1.9181748628616333,
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"learning_rate": 0.0005,
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"loss": 2.3365,
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"step": 3000
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},
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{
|
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"epoch": 0.1111111111111111,
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"grad_norm": 1.6642646789550781,
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"learning_rate": 0.0005,
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"loss": 2.2207,
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"step": 4000
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},
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{
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"epoch": 0.1388888888888889,
|
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"grad_norm": 1.1876742839813232,
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