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kmfoda commited on
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1 Parent(s): 2467ab2

Update with single epoch

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Files changed (2) hide show
  1. evaluate.py +12 -14
  2. results.json +1245 -0
evaluate.py CHANGED
@@ -11,12 +11,12 @@ test_indices_length = 10
11
 
12
  models = ["distributed/optimized-gpt2-250m", "distributed/gpt2-250m"]
13
 
14
- with open('./results.json', 'r') as file:
15
  results = json.load(file)
16
 
17
  for model_name in models:
18
 
19
- if (model_name not in results.keys()) or (model_name == "distributed/optimized-gpt2-250m"):
20
  results[model_name] = {}
21
 
22
  tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
@@ -24,8 +24,7 @@ for model_name in models:
24
  refs = list_repo_refs(model_name, repo_type="model")
25
  global_epoch = max([int(tag.name) for tag in refs.tags]) if refs.tags else None
26
 
27
- for epoch in range(0, global_epoch, 5):
28
- # for epoch in [global_epoch]:
29
 
30
  if str(epoch) in results[model_name].keys():
31
  continue
@@ -80,15 +79,14 @@ for model_name in models:
80
  results[model_name][str(epoch)] = [average_loss]
81
  print(f"Epoch: {epoch} Average Loss: {average_loss:.2f}")
82
 
83
- # breakpoint()
84
- with open("./results.json", "w") as outfile:
85
- json.dump(results, outfile, indent = 4)
86
 
87
- for model_name in models:
88
 
89
- plt.plot(results[model_name].keys(), results[model_name].values())
90
- plt.title(f"{model_name} Convergence Over Time")
91
- plt.xlabel("Steps")
92
- plt.ylabel("Loss")
93
- plt.xticks(fontsize=3.5)
94
- plt.savefig(f"{model_name.split('/')[1]}_results.png")
 
11
 
12
  models = ["distributed/optimized-gpt2-250m", "distributed/gpt2-250m"]
13
 
14
+ with open('results.json', 'r') as file:
15
  results = json.load(file)
16
 
17
  for model_name in models:
18
 
19
+ if (model_name not in results.keys()):
20
  results[model_name] = {}
21
 
22
  tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
 
24
  refs = list_repo_refs(model_name, repo_type="model")
25
  global_epoch = max([int(tag.name) for tag in refs.tags]) if refs.tags else None
26
 
27
+ for epoch in range(0, global_epoch):
 
28
 
29
  if str(epoch) in results[model_name].keys():
30
  continue
 
79
  results[model_name][str(epoch)] = [average_loss]
80
  print(f"Epoch: {epoch} Average Loss: {average_loss:.2f}")
81
 
82
+ with open("results.json", "w") as outfile:
83
+ json.dump(results, outfile, indent = 4)
 
84
 
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+ # for model_name in models:
86
 
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+ # plt.plot(results[model_name].keys(), results[model_name].values())
88
+ # plt.title(f"{model_name} Convergence Over Time")
89
+ # plt.xlabel("Steps")
90
+ # plt.ylabel("Loss")
91
+ # plt.xticks(fontsize=3.5)
92
+ # plt.savefig(f"{model_name.split('/')[1]}_results.png")
results.json CHANGED
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