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ahmadmwali
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m2m_trial1

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End of training

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  1. .gitattributes +1 -0
  2. README.md +22 -25
  3. all_results.json +14 -14
  4. config.json +32 -0
  5. eval_final_results.json +9 -9
  6. generation_config.json +9 -0
  7. logs/events.out.tfevents.1748457085.c1279aa5eb8f.2341012.0 +3 -0
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  23. model.safetensors +3 -0
  24. special_tokens_map.json +21 -107
  25. spiece.model +3 -0
  26. tokenizer.json +3 -0
  27. tokenizer_config.json +15 -921
  28. train_results.json +5 -5
  29. trainer_state.json +43 -253
  30. training_args.bin +2 -2
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README.md CHANGED
@@ -1,7 +1,6 @@
1
  ---
2
- library_name: peft
3
- license: mit
4
- base_model: facebook/m2m100_418M
5
  tags:
6
  - generated_from_trainer
7
  metrics:
@@ -18,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
18
 
19
  # m2m_trial1
20
 
21
- This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
22
  It achieves the following results on the evaluation set:
23
- - Bleu: 0.7038
24
- - F1: 0.8646
25
- - Wer: 0.1474
26
- - Cer: 0.0487
27
- - Meteor: 0.8523
28
- - Loss: 6.1316
29
 
30
  ## Model description
31
 
@@ -44,29 +43,27 @@ More information needed
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
47
- - learning_rate: 0.0005
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- - train_batch_size: 4
49
- - eval_batch_size: 4
50
  - seed: 42
51
- - gradient_accumulation_steps: 4
52
- - total_train_batch_size: 16
53
- - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
  - lr_scheduler_type: linear
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  - num_epochs: 3
 
56
 
57
  ### Training results
58
 
59
- | Training Loss | Epoch | Step | Bleu | F1 | Wer | Cer | Meteor | Validation Loss |
60
- |:-------------:|:-----:|:----:|:------:|:------:|:------:|:------:|:------:|:---------------:|
61
- | 6.1636 | 1.0 | 500 | 0.6810 | 0.8529 | 0.1720 | 0.0712 | 0.8387 | 6.1470 |
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- | 6.2279 | 2.0 | 1000 | 0.6980 | 0.8607 | 0.1520 | 0.0494 | 0.8476 | 6.1356 |
63
- | 6.1558 | 3.0 | 1500 | 0.7038 | 0.8646 | 0.1474 | 0.0487 | 0.8523 | 6.1316 |
64
 
65
 
66
  ### Framework versions
67
 
68
- - PEFT 0.15.2
69
- - Transformers 4.52.2
70
  - Pytorch 2.6.0+cu124
71
- - Datasets 2.14.4
72
- - Tokenizers 0.21.1
 
1
  ---
2
+ library_name: transformers
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+ base_model: castorini/afrimt5-base-ft-msmarco
 
4
  tags:
5
  - generated_from_trainer
6
  metrics:
 
17
 
18
  # m2m_trial1
19
 
20
+ This model is a fine-tuned version of [castorini/afrimt5-base-ft-msmarco](https://huggingface.co/castorini/afrimt5-base-ft-msmarco) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Bleu: 0.0
23
+ - F1: 0.0
24
+ - Wer: 1.0
25
+ - Cer: 0.9995
26
+ - Meteor: 0.0
27
+ - Loss: nan
28
 
29
  ## Model description
30
 
 
43
  ### Training hyperparameters
44
 
45
  The following hyperparameters were used during training:
46
+ - learning_rate: 0.0001
47
+ - train_batch_size: 16
48
+ - eval_batch_size: 1
49
  - seed: 42
50
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 
 
51
  - lr_scheduler_type: linear
52
  - num_epochs: 3
53
+ - mixed_precision_training: Native AMP
54
 
55
  ### Training results
56
 
57
+ | Training Loss | Epoch | Step | Bleu | F1 | Wer | Cer | Meteor | Validation Loss |
58
+ |:-------------:|:-----:|:----:|:----:|:---:|:---:|:------:|:------:|:---------------:|
59
+ | No log | 1.0 | 7 | 0.0 | 0.0 | 1.0 | 0.9995 | 0.0 | nan |
60
+ | No log | 2.0 | 14 | 0.0 | 0.0 | 1.0 | 0.9995 | 0.0 | nan |
61
+ | No log | 3.0 | 21 | 0.0 | 0.0 | 1.0 | 0.9995 | 0.0 | nan |
62
 
63
 
64
  ### Framework versions
65
 
66
+ - Transformers 4.50.0
 
67
  - Pytorch 2.6.0+cu124
68
+ - Datasets 3.4.1
69
+ - Tokenizers 0.21.1
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